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[Assistant] So, you're betting on whether the stock market is going to do better than the bond market. That's effectively what the plan was. Okay?


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[Assistant] And then you'd have to owe the government eight. Where is the government going to get the other two dollars from? It's going to reduce your social security contributions by two. So that's the government plan.


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[Assistant] Okay, so in the problem set, I gave you three problems. You can only do two of them now. The last one, I didn't get far enough to have you do, so just do two of them.


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[Assistant] And I'm going to give my own, uh, plan next time and also


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[Assistant] Do a little mathematics. It's going to turn out that it's quite interesting to, to math this up a little bit.


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[Assistant] Hi there, guys. My name is Richard McMunn from the career advisory and educational website, HowToBecome.com.


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[Assistant] Test, and I'm also going to give you free access to my online numerical reasoning test suite. So once we finish the tutorial, you can then start practicing within a few minutes.


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[Assistant] With my Online Numerical Reasoning Testing Suite, it's free of charge to use.


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[Assistant] And if you watch the video from beginning to end, you'll find out where to get access to that. Let's get straight into it.


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[Assistant] What do numerical reasoning tests cover? Well basically, numerical reasoning tests cover a wide range of mathematical formulas.


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[Assistant] Okay, so they can cover a diverse range of different kind of questions.


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[Assistant] My advice to you is to try and find out what kind of test questions you will be asked and what level of it's basic, intermediate or advanced before you go to your test, because otherwise you could spend literally weeks or months practicing the different variety of questions that you could get asked only to find that a lot of your preparation


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[Assistant] Was not worthwhile. So it is imperative to understand and practice the skills and knowledge required to work out the mathematics involved


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[Assistant] But my advice is to target your practice in the areas required.


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[Assistant] Now, most numerical reasoning tests contain questions in the following areas. Addition, subtraction, division, multiplying, fractions, percentages, decimals, ratios, charts and graphs.


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[Assistant] Mean mode, median range, areas and perimeters, number sequences, time,


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[Assistant] Conversions, measurements, money, proportions, formula, data interpretation, and quantitative data.


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[Assistant] Fractions, percentages and decimals. But for the more advanced kind of test question, you'll be looking at data interpretation, quantitative data. So as I say, it's really important to find out what


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[Assistant] Kind of numerical test you're required to undertake before you go through it.


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[Assistant] And this then enables you to target your practice on the right areas. And it's certainly worth trying to find out. Contact the test center and have a look at previous type of test questions to find out. Now, in the online testing suite, I am going to give you access to


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[Assistant] You will have all of these different kinds in there. So once you find out what kind of test you're going to be required to do, you can then tailor your practice accordingly.


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[Assistant] Let me give you some more tips before we get into some sample test questions.


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[Assistant] Now, during the numerical reasoning test, you will have a specific amount of time to answer each question. So you might, for example, it could say,


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[Assistant] You've got 30 minutes to answer 60 questions. Okay. And that's really important to understand what I mean by this. It's important that you do not spend too much time on one particular question. So you could start the test. Test question number one is relatively easy. Test


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[Assistant] Test question two is quite easy. You get onto three and it's difficult and you could freeze.


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[Assistant] And you could spend like a minute on that question, think on stealth to panic, when the best thing sometimes is to move on.


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[Assistant] So if you feel yourself spending too much time on a particular question, leave it, but make sure you leave a gap on the answer sheet, especially if you're required.


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[Assistant] To use a written answer sheet, make sure you leave a gap, because then all the ones after that would be out if you don't. Remember, the clock is ticking.


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[Assistant] So if you are stuck on a question, move on and come back to it at the end if you have time.


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[Assistant] Another numerical reasoning test tip. If there are 30 questions and you've just 20 minutes to complete the test, this gives you 40 seconds per question on average. 40 seconds is not a long time.


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[Assistant] And this is why it's really important to practice timed tests. Okay. This is why I'm giving you access to the suite.


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[Assistant] It's really important to practice under timed conditions, because when you get into the exam, some people…


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[Assistant] Not saying they panic, but they get anxious, they're worried and then they can't concentrate. Whereas if you've already practiced…


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[Assistant] I'm under timed conditions and you're more likely to perform to a higher standard.


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[Assistant] Okay, some more tips. Tip number three, try practicing numerical reasoning test questions in your head without writing down your workings out. This is really difficult to accomplish, but you will get better with practice and it's excellent for the real test preparation. Tip number four,


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[Assistant] Also practice numerical reasoning tests without a calculator. This will guarantee


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[Assistant] Tip number five, if you are permitted to use a calculator, it's a simple thing, but people don't realize this. Make sure you know how to use it.


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[Assistant] Cause you don't want to be there in the test cause a lot of test centers will give you a calculator.


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[Assistant] When you go in there, you're usually not permitted to take your own one because some people cheat. You can even buy some calculators now online.


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[Assistant] Where you can get, you know, people can send you the answer to questions on them. So a lot of test centers make sure, will insist you use their calculator.


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[Assistant] And they'll let you know what kind of calculator it is before you go to test. So you need to make sure.


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[Assistant] You know how to use one. Tip number six. Questions will often require you to identify what mathematical formula is being used.


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[Assistant] Okay. And that's one of the tricks and tips for getting higher marks is you read the question, you think, okay, I'm being assessed here with division.


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[Assistant] Now, before you answer the question, carefully read what the question is asking you and try and decide which mathematical formula you are being assessed against.


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[Assistant] Building confidence is a really important part of preparation stages, and the way that you do that is by watching videos like this.


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[Assistant] Undertaking different kinds of test questions, a whole variety of them.


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[Assistant] Okay, so let's now take a look at some sample numerical reason test questions.


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[Assistant] So I'm going to work through, some are easy, some are more difficult. I'm going to give you the answers to the majority of them and explain how to reach the answer. But you will also find during some of the questions, I'll say to you, please work it out yourself.


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[Assistant] And put the answer in the comments section below the video. So what you can do when it gets to a question where I'm asking you to work it out is to please pause the video, have a look at the question, work through it in your own time.


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[Assistant] And then put your answer in the comments section below, and then you can get the answer by accessing the online Numerical Reasoning Test section.


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[Assistant] Here's some test questions. Number one, question one, what is 45% of 500? A relatively simple question. Okay.


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[Assistant] But unless you know how to work out percentages, then you're not going to understand it. So here's how to work it out. Divide the whole number, 500, by 100 for the percentage, and then multiply the percentage you want to find.


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[Assistant] For example, 500 divided by 100 for the percentage equals 5 multiplied by 45 percent equals 225. So, 225 is 45 percent of 500.


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[Assistant] Okay, so the answer is 225, and you'll find that as we go through


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[Assistant] These tests, there will also be some multiple choice ones, which a lot of people think multiple choice is easier. Not necessarily the case, because some of them are really close. Question two, a charity arranges a bike race. Okay. And 120 people take part.


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[Assistant] A third of the people finished the race in under half an hour. How many people finished the race in 30 minutes or more? Bit of a… not a trick question, but you can get caught out. So, what we need to do is to work out a third of 120


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[Assistant] Okay, which equals 40 because 40 people finished it in under half an hour. Only people finished the race in 30 minutes or more, or two thirds did. So therefore, two thirds is 80. Okay. So if you need to watch that again and listen to that again, then please pause it or watch it once I finished. Question number three. What is the volume of that shape? Okay. Relatively simple.


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[Assistant] And in this particular instance, we need to work out 7 x 7 x 7.


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[Assistant] Equals 343 centimeters cubed.


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[Assistant] Okay, centimeters cubed, because it's three-dimensional.


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[Assistant] This is a multiple choice option. We've got A, B, C, D or E.


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[Assistant] And the answer is, so you can see it's going to be round about 3.2, round about that. So the answer is 3.18.


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[Assistant] So you can eliminate C and D straight away, because you can see 6.47 minus 3.29. It's not going to be 4. So it's either A, B or E.


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[Assistant] And the answer is E. Okay, question number five. What is 9 11th of 88? Let's take a look at how we work this out. Step one, 88 divided by 11.


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[Assistant] Equals 8, because we're trying to find out 9 11ths of 88. So we need to work out what 11 11ths is. So 11 11ths is 88, but one 11 is 8.


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[Assistant] And then we multiply that by 9 to get the answer 72. Therefore, the answer is D, 72. Relatively simple. Question 6.


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[Assistant] These can be easy, these type of questions, when you're looking for the next in the sequence, and they can be difficult as well. Some of them are really hard.


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[Assistant] Let's have a look at this one. What two numbers come next in the sequence? We've got 2, 4, 8, 16, 32, 64.


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[Assistant] So I want you to work this out yourself. Let's go straight in at the deep end.


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[Assistant] So put your answer in the comments section below the video to question 6. What two numbers come next in the sequence? You've got 2, 4, 8, 16, 32, 64. Is it A, 126 and 215?


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[Assistant] It does on Facebook you look difficult because there's more information, but when you break it down, it's relatively simple.


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[Assistant] A family of four people split the cost of all the household bills equally. The water bill is £80.40, the gas bill £35.


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[Assistant] Electric bill 40 and the rent for the month was 490. How much does each member of the family put towards covering all the bill costs? What we need to do?


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[Assistant] Step one is add up all of the household bills, so we would add 80.40, 35, 40,


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[Assistant] And then 490, we would then divide that by four for each person to reach the answer. And the correct answer is C, 161.35. Question eight.


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[Assistant] This is a kind of data interpretation numerical reasoning test question. So we see across the top employees in departments of a particular company.


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[Assistant] Then we've got the different departments for marketing, admin, sales and IT. Then we've got the six month period, January, February, March, April, May.


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[Assistant] June and then the employee numbers in each department. So the question is, what was the average number of admin employees over the six month period?


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[Assistant] To the nearest whole number, which tells me that the answer is probably not going to be to the nearest whole number. So we're going to have to round it up or down. So we need to choose


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[Assistant] Add up the total number of admin workers for the six-month period, which is there. So we just add those up 88.


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[Assistant] Step two, divide the total number of admin workers for the six-month period by six months.


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[Assistant] And the answer is 14.666 recurring.


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[Assistant] It's the same table, the employees in departments of a company, but the question is difference. What is the difference between the total number of employees in marketing


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[Assistant] And the total number of employees in sales across the six month period. Multiple choice


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[Assistant] 21, 26, 31, 28 or E35. And I'd like you to calculate this for me, please.


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[Assistant] Put your answer in the comments section below the video. So say Question 9 answer is A, B, C, D or E.


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[Assistant] What is the difference between


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[Assistant] And the total number of employees in sales across the six-month period.


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[Assistant] I can say again, if you need time to work it out, please pause the video. Question 10. This is BMW sales. The above table shows the sales across six countries for the model BMW for a six month period.


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[Assistant] The BMWs are imported to each country from a main dealer. Use the information provided to answer the following questions.


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[Assistant] What percentage of the overall total was sold in April? So what we need to do is look at April.


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[Assistant] So to work out the percentage overall total that was sold in April, divide how many BMWs were sold in April, which is 189, by the total


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[Assistant] I'm out, which is 1149 and then multiply it by 100.


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[Assistant] So 189 divided by 1149 times 100.


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[Assistant] And the correct answer is 16.4%. Question number 12. Another kind of question which is a scatter graph


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[Assistant] This shows the number of driving lessons and the number of tests taken to pass. What percentage of the total people who took the test passed at the first attempt?


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[Assistant] Up here on the left, you need to look at the information, number of tests to pass. So you've got one, two, three, four, five, six, seven.


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[Assistant] And across the bottom, the number of driving lessons. So we could have a variety of questions based around this category. But the question is, what percentage of the total people who took the test passed at the first attempt? So, step one.


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[Assistant] We need to count the total number of people who took the test if we add up all of those dots. There's 10.


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[Assistant] And then we need to count the number of people who pass at the first attempt, which is, of course, the bottom one there. One, two, three. And then what we need to do is work out the percentage, which is 30%. Question 13.


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[Assistant] Look carefully for the pattern and then choose which pair of numbers comes next.


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[Assistant] So it's quite difficult to work out the pattern here, but I can see straight away. You've got zero there. You've got one. Okay. So this is called


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[Assistant] A Fibonacci number sequence, and the answer is 13 and 21. Now, the sequence follows the pattern of adding the two previous numbers together in order to get the next number. For


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[Assistant] The 8 is found by adding the 5 and the 3 together, and so forth.


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[Assistant] Two previous numbers, 0 plus 1 is 1, 1 plus 1 is 2, 2 plus 1 is 3, 3 plus 2 is 5, 5 plus 3 is 8. 8 plus 5 means it's 13 would go there. The first one 13 plus 8 is 21. Okay, so you need to be cute and smart and look for the sequence. Number 14. This is your turn.


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[Assistant] Now, the probability of picking a lottery winning ticket in the national lottery is 1 in 14 million. If 36 million tickets are sold weekly,


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[Assistant] How many jackpot winners on average would you expect in one week?


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[Assistant] And again, put your answer in the comments section below. So say question 14, answer is A, B, C or D.


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[Assistant] Again, if you need to pause the video, please do. The probability of picking a lottery winning ticket in the national lottery is 1 in 14 million. If 36 million tickets are sold weekly, how many jackpot winners on average would you expect in one week? Question 15. This is slightly harder. A function is represented by the following machine. So we can see here that 9 is put into the machine and the output of the machine is 126. And in the middle,


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[Assistant] We have plus 12, so 9 plus 12, and then we need to work out what goes here.


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[Assistant] In the second part of the sequence to get to 126 and we've got


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[Assistant] Five answers. A multiplied by 12. B divided by 12. C multiplied by 6. D divided by 6. E minus 8. So, how to work it out? 9 plus 12.


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[Assistant] Okay, and then we need to work out the question mark there to reach 126. So 9 plus 12 is 21.


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[Assistant] 126 divided by 21 equals 6, and therefore the answer is multiplied by 6. So 9 plus 12


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[Assistant] Multiplied by 6 equals 126. Relatively simple. I'm going to give you one of these to do now. So a function is represented by the following machine.


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[Assistant] You've got the input to the left multiplied by 7 minus 6 equals the output. A number is put into the machine. The output of the machine is 71. What was the number inputted into the machine?


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[Assistant] So put your answer in the comments section below. Say question 16. The answer is… and I've not given you any choices there.


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[Assistant] So you need to decide the correct answer. Again, if you need to pause the video, please do to work it out. Again, try and work it out in your head.


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[Assistant] So question 17, what is 48% of 900? How do we reach this answer? 900 divided by 100, for the percentage is 9.


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[Assistant] 48 times 9 equals 432. So the answer is B. Relatively simple if you know how to work out simple percentages. Question 18. Slightly more harder now. Work out the area of the shape. Write your answer in centimeters squared. It's because it's two-dimensional. Step one.


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[Assistant] How to work this out? Split the shape up in two rectangles as follows, because otherwise it would be


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[Assistant] Harder to work this out. I mean, I'll give you another way in a sec. I'll tell you now what you could do.


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[Assistant] Is you could work out 500 times 300 to give you your answer.


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[Assistant] And then you would subtract from it a hundred centimeters for there by 400. But we're going to do it this way.


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[Assistant] So split the shape up into two rectangles as follows. You've got shape one and you've got shape two. So just work those out. Okay. So we can see that


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[Assistant] Shape two is 500 by… we need to work out this part here. So all the way up to the top is 300 minus 100. That's 500 by 200. And shape one is 100 from there to there.


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[Assistant] We need to work out this part. Well, if that part's 400, that's five. That means that part across the top is a hundred.


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[Assistant] So, calculate the area of each shape individually. Shape 1, 100 times 100 equals 100 squared. Shape 2, 500 by 200 is 1000. Then we just add them together.


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[Assistant] The correct answer is 1100 cm2. Relatively simple. Now it's your turn.


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[Assistant] Work out the area of the shape and write your answer in meter square. So please put your answer in the comments section below the video.


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[Assistant] And you can use either one of the options that I've just taught you and shown you. So again, if you need to pause the video, please do. Question 20. How many different numbers can be made


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[Assistant] From these 4 playing cards. Tricky question. 4931.


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[Assistant] Now this can be done for all four numbers. If you start with a different number, you will be able to make six different numbers. Therefore, six groups of four equals 24.


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[Assistant] So to shortcut this, you just need to work out how many.


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[Assistant] You can get from one of the numbers, starting at the beginning, the four, and then just multiply it by four. It saves time working out all of them. And you could quite easily see how you would spend literally a couple of minutes working this out


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[Assistant] Unless you did it a savvy way by just working out one of them and then multiplying it by four. Question 21.


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[Assistant] Now this is a tricky one. It's easy, really, but it's tricky because people get caught out, and I bet a lot of you will do. How many number fours are there between 1 and 100? So, you need to count how many number fours. So, 4 is 1, 14 is 2, 24 is 3, and you do the rest. So, tell me the answer in the comments section below the video. Is it A, 18? B, 19? C, 20? D, 21?


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[Assistant] How many number fours are there between 1 and 100? And again, pause the video if you need to.


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[Assistant] Okay, so what I'd like you to do now, guys, that's 21 sample questions. I want to take you on another journey and give you more now.


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[Assistant] Please, first of all, I'd really appreciate it if you give the video a thumbs up.


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[Assistant] That would motivate me to do more for you, more free videos and give you more free access. Please SUBSCRIBE to the channel because you'll then get notified when I create videos like this and we do a whole raft of videos from how to become. Don't forget to put your answers in the comments section below.


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[Assistant] But also click the link below the video in the description. You can go through to the page where you can get free access to that numerical testing suite I was talking about.


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[Assistant] Okay, we cover numerical testing, psychometric testing. It's really helpful. Lots of people use it to help them pass their tests.


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[Assistant] Click the link right now below the video. Thank you very much for watching, guys. I've really enjoyed it.


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[Assistant] I look forward to answering your responses and your, sorry, to marking your answers to the questions below the video.


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[Assistant] And I hope you enjoyed the testing suite and good luck in your pursuit to passing your numerical reasoning test.


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[Assistant] And I'm thrilled to be here and share some prompting best practices with you all.


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[Assistant] First, you'll learn best, some prompting best practices for software development. Then we'll cover some common use cases, summarizing, inferring, transforming, expanding, and then you'll build a chatbot using an LLM.


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[Assistant] Lesson 79 By Air


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[Assistant] We're stage agnostic, so, you know, a lot of VCs these days are stage agnostic. I think many of them started out as kind of early stage, but early stage is a little bit out of favor because


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[Assistant] Capital requirements and a lack of liquidity have inhibited a lot of firms from doing very, very early. It just takes a long time to go from startup idea to a liquidity event.


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[Assistant] And today, the latest average from NVCA, the Natural Adventure Capital Association, is 8.7 years.


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[Assistant] So you're investing over the long haul. Better to get a later stage company where you can make a quick return.


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[Assistant] It's actually a pretty small number. You know, our objective for equity is to produce strategic impact, to help us sell more silicon into new geographic markets, to help us enter new markets, you know, whether it's entering the embedded space or entering the smartphone space, both areas that we haven't done a lot in historically.


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[Assistant] Hello there, my name is Richard McMunn from the interview training website, PassMyInterview.com. And in this tutorial, I will teach you how to pass an Amazon interview. And in particular, I will give you my TOP 11 Amazon interview questions and answers.


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[Assistant] So, if you have an interview coming up with Amazon for any role whatsoever, make sure you stay tuned because I will help you to succeed. And to achieve that goal, this is what I will cover.


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[Assistant] So, I will give you a list of Amazon interview questions that I strongly recommend you prepare for. And these are suitable for all Amazon job roles.


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[Assistant] I will also give you example answers to difficult Amazon leadership principles interview questions. I will give you some really important tips on how you can stand out during your Amazon interview. And I will also


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[Assistant] Today, I'm going to tell you how you can access further resources, including these slides to help you succeed. And just very quickly, please do make sure you SUBSCRIBE to this channel


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[Assistant] We have over half a million subscribers now and lots of you are passing your interviews as a result of the content. I don't want you to miss out. You can also connect with me on LinkedIn


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[Assistant] I put my LinkedIn link in the description below the video. And it's always great to connect with like-minded professionals such as yourself. And please give the video a LIKE, because that tells me you find the content useful. Thank you very much. The first question that I want you to prepare an answer to is tell me about yourself. Now, in your answer to this first Amazon interview question,


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[Assistant] Focus on the different skills, qualities and experiences you have that are a match for the role you are applying for. And you should also be positive in your answer. And remember, you may need to back up your claims of how you work later in the interview. So here's a great example answer to assist you. Tell me about yourself.


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[Assistant] I am a self-motivated and high achieving employee.


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[Assistant] Now over the years, I've built up lots of transferable skills and experiences that are a match for not just this job description.


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[Assistant] But also for the leadership principles you expect your employees to demonstrate in their


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[Assistant] For example, I will always use my initiative to come up with new ideas for the team.


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[Assistant] But I genuinely believe I am the right person for the job based on my passion.


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[Assistant] My experience and my commitment to helping the organization I am a part of be the best it can be." Now, that is a brilliant, positive answer to that first Amazon interview question. Tell me about yourself. Now, you can either pause the video if you want to


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[Assistant] Where you can download my full set of Amazon interview questions and answers, including the ones we are covering today within this presentation.


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[Assistant] The next question. Why do you want to work at Amazon? Now, this question is almost guaranteed to feature at some stage during your Amazon interview. And in your response, give genuine


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[Assistant] And unique reasons why you want to work for this brilliant organization. Here's my example answer to help you. Why do you want to work at Amazon? I want to work at Amazon because in my opinion, it is the greatest company in the world and I feel I will be able to learn, grow and develop


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[Assistant] Whilst working alongside other self motivated people. Now, Amazon has led the way for many years now, not just in the quality products and services it offers,


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[Assistant] But how it delivers its products to consumers and how it always puts customers at the forefront of everything it does. And I can't think of many other companies that start with the customer and then work backwards.


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[Assistant] Now another reason I want to work at Amazon is because of your leadership principles. If I demonstrate these in my work, I will reach my full potential and I will get to achieve some pretty amazing things whilst I am working here. So that is a really strong answer.


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[Assistant] That explains why you want to work at Amazon. Now, within that response, I talked about the leadership principles. We will touch


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[Assistant] On those more as we progress through this tutorial, and I believe…


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[Assistant] If you want to pass your Amazon interview, you need to learn and understand the leadership principles. It won't take you long to do it. But again,


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[Assistant] Wait as we progress through this tutorial because I will talk more about them as we go along. Now, don't go anywhere because I still have more questions and answers to give you to help you pass your Amazon interview. But when you are ready, if you want to click that link that has appeared


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[Assistant] In the top right hand corner of the video, it will take you through to my website, PassMyInterview.com, and you can download my full set of Amazon interview questions and top-scoring answers, including the ones we are working through together today. But here's the next question. Tell me about a time when you improved a process? Now, this behavioral interview question


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[Assistant] But I managed to make a significant improvement to one of the processes in my previous company.


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[Assistant] We have been sending out company invoices by post. Now it was a tedious and lengthy process, and many of our customers would use the excuse that they hadn't received the initial invoice to not pay on time.


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[Assistant] Now, this frustrated me because the company was losing out on revenue and it was not helping cash flow. Now I decided to use my initiative


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[Assistant] I came across the online invoicing platform called FreshBooks. I looked into the service


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[Assistant] And I then presented my idea to my manager. Now, after a few discussions, we started using FreshBooks for our invoicing processing. And soon after payments started being made by our customers on time, which significantly improved company cash flow. So that response shows that you care.


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[Assistant] And you then use your initiative to improve a process that is of benefit to the organization. So it's a really strong example.


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[Assistant] The next question. What are your strengths? Now, my advice is to name several different strengths that are a match for the job description.


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[Assistant] And the Amazon leadership principles. So here's another really good answer to help you in your preparation. What are your strengths?


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[Assistant] My strengths include my ability to always put the needs of the team first.


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[Assistant] Other strengths include my innovative approach to tasks, my fast pace of working


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[Assistant] And my understanding that all employees must look to help a company save money as opposed to spending it without due care or attention. So that's another really good answer. You are listing a few strengths there.


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[Assistant] That in my opinion are aligned to the Amazon leadership principles. We will cover the what's your biggest weakness question later on. So make sure you stay tuned for that, because that is a tough question to answer. Here's the next one.


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[Assistant] Now going above and beyond what is normally required is a sign of a great employee.


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[Assistant] And take responsibility when the pressure is on. So here's my example answer to help you. Tell me about a time when you did something that was outside of your responsibility at work. I can recall quite recently


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[Assistant] I was working as part of a team and it was late on a Friday afternoon when the company website went down for no apparent reason.


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[Assistant] Now we had an online sale plan for the following Monday morning, so this was potentially a disaster for the company.


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[Assistant] Now my manager asked for volunteers to stay behind late that evening to try and get the website back up and running. And I volunteered to help.


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[Assistant] Now she gave me the task of trying to find an online contractor who could help us solve the problem. Now, despite having zero experience in this area.


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[Assistant] I put a plan of action in place and I then got to work.


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[Assistant] So I managed to find a freelance IT developer on the website Upwork.com and I started communicating with them online explaining what the issue was and trying to help him establish the root cause. Now, eventually we managed to find the issue. The website had been hacked due to the fact the plugins had not been updated for some time.


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[Assistant] Now by 6pm that evening, the website was fully functioning again, which was great news for the pending company sale.


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[Assistant] Now if something is outside of my responsibility, I will still take on the task as it is an opportunity to do something new and develop wider skills.


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[Assistant] That's a really good answer to that difficult behavioral interview question for Amazon. Tell me about a time when you did something that was outside of your responsibility at work? The next question. How would you react if the people in your team


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[Assistant] Do not agree with your opinions or your ideas. Now, this is a difficult Amazon interview question to respond to, and it can only be answered correctly if you understand the leadership principles.


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[Assistant] Here's a great way to respond to this difficult Amazon interview question.


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[Assistant] How would you react if the people in your team do not agree with your opinions or your ideas? Here we go. This would not phase me at all.


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[Assistant] Providing I had explained my ideas or opinions in a concise manner and I had challenged them professionally, I would then commit to the team consensus. The team must always come first, and whilst I do believe I am good at what I do, I am not perfect and I still have lots to learn.


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[Assistant] In a recent team meeting, we were discussing ways to promote a new company product and I put forward suggestions for trying social media advertising as a way to market the product. Now, I felt we had the opportunity to reach a new and fresh audience online, but nobody else in the team agreed this was a good idea. I challenged them by explaining the benefits of online advertising, but they were still not keen.


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[Assistant] Now, although I disagreed with them, I positively committed to the overriding team opinion and the agreed marketing strategy. That, in my opinion, is the perfect way to answer that difficult Amazon interview question. How would you react if the people in your team do not agree with your opinions or your ideas?


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[Assistant] The next question. Tell me about a time you had to deal with a difficult customer or client.


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[Assistant] This is a challenging Amazon interview question to answer. Remember, Amazon always puts the customer first.


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[Assistant] So here's how I would answer this Amazon interview question.


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[Assistant] Tell me about a time you had to deal with a difficult customer or client? In a previous job I had the responsibility


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[Assistant] of speaking to clients and customers on the telephone on a regular basis. Now, one situation comes to mind


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[Assistant] Who does not take things personally? And I knew how important the client was to the business, so I went out of my way to try and build a good relationship with him.


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[Assistant] I asked him questions about what was important to him and I tried to find a common connection as this would help improve communications between us.


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[Assistant] I was firm in respect of sticking to the agreed project specification, but where possible, I tried to explain to him the benefits of the work we were doing and how these would help his business moving forward. By remaining calm and professional,


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[Assistant] And by trying to improve the relationship over time, I managed to win him around and he became a long standing client of the company. Always remember…


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[Assistant] Amazon puts the customer first. They will do everything they can to provide brilliant products and services that meet the needs of the customers. I like that answer.


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[Assistant] Because you are not giving in to his demands, but instead you are using effective communication skills and relationship building skills to get the outcome that you want for the company you are working for.


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[Assistant] The next question. Tell me about a time when you took a risk at work? Wow, this is a difficult one. Now, some people


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[Assistant] We'll say they don't take risks at work when answering this difficult Amazon interview question. But I don't think that's the correct way to respond to the question. Here's how I would personally answer this challenging Amazon interview question. Tell me about a time when you took a risk at work?


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[Assistant] I was working on a project that had a really tight deadline.


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[Assistant] Now, to meet the project deadline, I was working over the weekend, but unfortunately, my company laptop developed a fault and I could no longer use it. Thankfully, I'd backed everything up as I worked on the iCloud, but I now didn't have the laptop to work on.


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[Assistant] Now, any product purchases over $500 had to be approved by my manager, but he wasn't contactable. I decided to take the risk and buy a new laptop that same day because I knew if I waited for Monday to get approval, the deadline would not be met and this would reflect negatively on the business.


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[Assistant] Now, whenever I take a risk, it is always calculated and I will only take one if I feel it is to the benefit of the company. Now, I believe


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[Assistant] To work at Amazon, you should be prepared to take calculated risks that are in the interests of the company. So I would not say I don't take risks at work. I would use an example like that


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[Assistant] Where I am taking a risk that is calculated and it is important that I take the risk because otherwise the company loses out.


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[Assistant] Here's that difficult question that I mentioned earlier. What's your biggest weakness? Now, whilst it is important to give an honest and genuine weakness,


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[Assistant] Try not to give one that is a match for the person specification for the role you are applying for at Amazon. Here's a great way to answer this question. What's your biggest weakness? My biggest weakness is the fact


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[Assistant] I am not that confident yet when giving presentations. I was asked to give a presentation in a previous job and despite preparing well for it, I was quite nervous. Now, although giving presentations is not part of my everyday work, I still want to improve in this


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[Assistant] I have been reading a book called HOW TO DELIVER A GREAT TED TALK by Akash Korea.


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[Assistant] Now my attitude to self-development is positive and I genuinely believe it does not matter how old you are.


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[Assistant] Or how much experience you have, there is always something new to learn.


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[Assistant] I believe that's a safe weakness to give. And you are also providing proof of how you are taking steps to improve. If you do mention that you are reading a book,


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[Assistant] Make sure you do get a copy of it and read it because they may have read it and they may ask you questions about it.


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[Assistant] The next question. Tell me about a time when you showed initiative at work? This is a difficult one. Now, being able to use your initiative is a great way to demonstrate you have what it takes to follow the 14 Amazon leadership principles. So here's a great way to respond to this question. Tell me about a time when you showed initiative at work?


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[Assistant] In a previous company I was working for, we had a relatively high turnover of staff due to the nature of work. Each time a new member of staff joined the team, they needed to be trained up in how to use our company's systems. This training took time


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[Assistant] To create a training folder that included different modules and clear instructions on how to use the company's systems.


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[Assistant] Now at the end of the training modules, I created a short quiz that tested the user's ability to operate these systems safely and competently. Now, my manager praised me for coming up with this idea because it saved the company lots of time and resources moving forward.


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[Assistant] That is a cracking answer to that question. Tell me about a time when you showed initiative at work.


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[Assistant] Where do you see yourself in five years? Well, again, this is a common Amazon interview question and one I believe needs to be answered in a specific way. Here's how I would answer this question. Where do you see yourself in five years? I see myself still working here at Amazon.


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[Assistant] Either in the same role or having gained advancement to a higher level.


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[Assistant] I am also someone who is keen to continually improve and develop professionally, so in five years from now, I see myself as a fully competent and loyal Amazon employee who has a diverse set of skills and qualities that can be used to help the team I am a part of achieve its goals." Another really concise and positive response.


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[Assistant] Now the next thing to do is make sure you CLICK THAT LINK RIGHT NOW in the top right hand corner of the video. Head over to my website, PassMyInterview.com.


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[Assistant] And you can download my full set of Amazon interview questions and answers, including the ones we have covered today within this presentation. I have also placed links


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[Assistant] to other Amazon interview videos right here on YouTube in the description below the video. Make sure you check those out. I hope you've enjoyed that


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[Assistant] And you can connect with me on LinkedIn. I've put my LinkedIn link in the description below the video. And don't forget to give the video a THUMBS UP! Because as I said,


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[Assistant] That motivates me to create more for you. Thank you for watching and I genuinely wish you all the best for passing your Amazon interview. Have a brilliant day!


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[Assistant] You can do this in the chat GPT web interface. I do this all the time to summarize articles so I can just kind of read the content of many more articles than I previously could. And if you want to do this more programmatically, you'll see how to in this lesson.


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[Assistant] Row, row, row your boat. Gently down the stream.


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[Assistant] This is really powerful because it starts to combine these language models with data that they weren't originally trained on.


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[Assistant] So it makes them much more flexible and adaptable to your use case. It's also really exciting because we'll start to move beyond language models, prompts, and output parsers and start introducing some more of the key components of LingChain, such as embedding models and vector stores.


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[Assistant] We're going to import the retrieval QA chain. This will do retrieval over some documents. We're going to import our favorite chat open AI language model. We're going to import a document loader. This is going to be used to load some proprietary data that we're going to combine with the language model. In this case, it's going to be in a CSV. So we're going to import the CSV loader. Finally, we're going to import a vector store.


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[Assistant] There are many different types of vector stores and we'll cover what exactly these are later on.


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[Assistant] This is really nice because it's an in-memory vector store and it doesn't require connecting to an external database of any kind, so it makes it really easy to get started. We're also going to import display and markdown to


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[Assistant] As we can see below, there will only be a few lines of code to create this.


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[Assistant] First, we're going to specify the VectorStore class. As mentioned before, we're going to use this VectorStore as it's a particularly easy one to get started with.


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[Assistant] After it's been created, we're then going to call from loaders.


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[Assistant] Which takes in a list of document loaders. We've only got one loader that we really care about, so that's what we're passing in here.


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[Assistant] After it finishes, we can now take a look at what exactly it was returned.


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[Assistant] Embeddings create numerical representations for pieces of text.


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[Assistant] This numerical representation captures the semantic meaning of the piece of text that it's been run over.


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[Assistant] Pieces of text with similar content will have similar vectors. This lets us compare pieces of text in the vector space. In the example below, we can see that we have three sentences.


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[Assistant] The first two are about pets. Well, the third is about a car.


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[Assistant] If we look at the representation in the numeric space, we can see that when we compare the two vectors on the pieces of text corresponding to the sentences about pets, they're very similar.


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[Assistant] The next component that we're going to cover is the vector database.


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[Assistant] When we get a big incoming document, we're first going to break it up into smaller chunks.


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[Assistant] We then create an embedding for each of these chunks, and then we store those in a vector database. That's what happens when we create the index.


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[Assistant] Well let's now do it a bit more step by step and understand what exactly is going on under the hood. The first step is similar to above.


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[Assistant] To create embeddings, we're going to use OpenAI's Embedding class. We can import it and initialize it here. If we want to see what these embeddings do,


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[Assistant] We want to create embeddings for all the pieces of text that we just loaded, and then we also want to store them in a vector store. We can do that by using the from documents method on the vector store. This method takes in a list of documents, an embedding object, and then we'll create an overall vector store.


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[Assistant] We can now use this vector store to find pieces of text similar to an incoming query.


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[Assistant] We can see that it returns four documents, and if we look at the first one,


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[Assistant] First, we need to create a retriever from this vector store. A retriever is a generic interface.


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[Assistant] That can be underpinned by any method that takes in a query and returns documents. Vector stores and embeddings are one such method to do so, although there are plenty of different methods. Some less advanced, some more advanced.


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[Assistant] Next, because we want to do text generation and return a natural language response, we're going to import a language model and we're going to use ChatOpenAI. If we were doing this by hand, what we would do


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[Assistant] is we would combine the documents into a single piece of text.


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[Assistant] So we'd do something like this, where we join all the page content in the documents into a variable.


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[Assistant] This does retrieval and then does question answering over the retrieved documents. To create such a chain,


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[Assistant] There are a few other methods that you can use to do question answering that I'll maybe touch on at the end, but we're not going to look at in detail. Third, we're going to pass in a retriever.


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[Assistant] When we get the response, we can again display it using the display and markdown utilities.


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[Assistant] So, these two things equate to the same result. And that's part of the interesting stuff about linkchain. You can do it in one line, or you can look at the individual things and break it down into five more detailed ones. The five more detailed ones let you set.


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[Assistant] And so if you remember when we created it by hand, we specified an embedding. And we can specify an embedding here as well. And so this will give us flexibility over how the embeddings themselves are created. And we can also swap out the vector store here for a different type of vector store.


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[Assistant] So there's the same level of customization that you did when you created by hand that's also available when you create the index here.


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[Assistant] We use the stuff method in this notebook. The stuff method is really nice because it's pretty simple. You just put all of it into one prompt and send that to the language model and get back one response. So it's quite simple to understand what's going on. It's quite cheap and it works pretty well. But that doesn't always work okay.


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[Assistant] But what if you wanted to do the same type of question answering over lots of different types of chunks?


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[Assistant] Then there are a few different methods that we can use. The first is MapReduce. This basically takes all the chunks


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[Assistant] Passes them along with the question to a language model, gets back a response, and then uses another language model call to summarize all of the individual responses into a final answer.


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[Assistant] This is really powerful because it can operate over any number of documents.


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[Assistant] for combining information and building up an answer over time. It will generally lead to longer answers and it's also not as fast because now the calls aren't independent. They depend on the result of previous calls.


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[Assistant] MapRerank is a pretty interesting and a bit more experimental one where you do a single call to the language model for each document and you also ask it to return a score. And then you select the highest score.


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[Assistant] This relies on the language model to know what the score should be. So you often have to tell it, hey, it should be a high score if it's relevant to the document and really refine the instructions there.


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[Assistant] Similar to MapReduce, all the calls are independent, so you can batch them, and it's relatively fast.


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[Assistant] The second most common is the MapReduce method, which takes these chunks and sends them to the language model.


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[Assistant] For example, a really common use case of the MapReduce chain is for summarization, where you have a really long document and you want to recursively summarize pieces of information in it. That's it for question answering over documents.


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[Assistant] Hello again and welcome to the second video tutorial on intro web. In the last video I have introduced intro web framework and we have explored them application.


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[Assistant] So in this video, I'm going to show you full common features of this intro web framework.


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[Assistant] So, let's get started. IntroWeb is a framework for web development in Delphi. IntroWeb allows the Delphi developers to create applications in a true, red manner by dragging and dropping components on an IntroWeb form, or IW form. IntroWeb is designed to build any sort of web application.


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[Assistant] Whether it's a simple data entry form, a poll, or a complex application, where clients have to be logged in for an extended period of time.


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[Assistant] Interweb works much like a normal executable application, with the exception that the user interface is a web browser instead of a window.


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[Assistant] The Server Controller. The Server Controller unit is where you can control general aspects of your web application. For instance, if you want to use compression or the templates folder, our application reacts if your user is using an unsupported browser.


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[Assistant] So in general, you don't need to add code to the server controller.


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[Assistant] But if you need custom controller of a specific aspect of your application, a good reason for customizing the server control is preparing your application to support search engines. And how we can access the server controller?


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[Assistant] Session. From interweb version 14, user session also contains web application property. You must check this property for nil value before using it. Interweb web application types.


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[Assistant] When we talk about interweb application types, we are basically talking about deployments. For example, how you can install your interweb application to be available to your users. Otherwise, all the interweb application types are the same. Currently, interweb has few types of applications. For example, standalone server type.


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[Assistant] ISAPI type and SA server. The SA server is a web application that includes an embedded web server, the interweb core code, and a UR code. The main goal of the SA server is to allow the developers easily deploy the application without all issues of installing and configuring a web server like IAS or Apache.


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[Assistant] As the SI server includes its own web server. It is an indie-based web server.


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[Assistant] For an ISAPI DLL, you need to set up IIS or Apache to host your application. The main advantage of the ISAPI deployment is that you don't need to worry about which port your application will be listening to.


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[Assistant] As you are running under IaaS, all the connections are made on port 18 and IaaS can host multiple IaaS API DLLs.


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[Assistant] So let's understand the basic process of the user interaction with the IntroWeb application. Your IntroWeb application is running on your server. It can be ISAPI-TLL or a SA server. Your server must have an IP which is accessible by your user through your network or the internet.


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[Assistant] You can also have a domain name that translates or points to your server The user types the IP address or port of your web application on the browser or simply the URL of your website


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[Assistant] The interweb application receives the request, processes it, renders the interweb form and sends it back to the browser. That tells the browser how to render your interweb form.


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[Assistant] For example, browser sends the button click information to the interweb application running in your server and the process repeated again.


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[Assistant] So it's time to demo. So now we can start by creating a new project. I select another project and intro web. This is intro web application wither. And we can select, okay. Can name this project. Demo IB.


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[Assistant] Guessing game. Now I'm going to make a guessing game on the Interweb web framework. So I select this standalone application type. So, click the OK button. And we have to confirm it. Yes, this is the main program. This is the user session.


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[Assistant] And this is our UI. On the interweb, we can only drag and drop our interweb components. It's InterwebStandard, InterwebControl, InterwebData, and InterwebAuthentication.


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[Assistant] So I select this interrupt standard, and one button, another button, and edit.


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[Assistant] IW memo, this one, and IW label. So now we can design this application.


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[Assistant] So we can rename it to check.


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[Assistant] Start a new game. Okay. Now we can select this interweb form. And we have to create uncreate event. And we have to enable randomizing.


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[Assistant] And I'm going to declare two variables. Global variables. It's x and y. Integer.


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[Assistant] x equals 0, it's the initialization part. And x equals random range, it's 100. Okay. Now we can create


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[Assistant] And this is the less than x and h.


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[Assistant] The guested number is 17 and you found it. And we can start a new game by clicking this button. New game is started. Okay. And we can play it again.


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[Assistant] So, that's it. In the next video tutorial, we will learn Unigui web-paramark in Dolby.


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[Assistant] One of the problems of object detection as you've learned about it so far is that your algorithm may find multiple detections of the same object. So rather than detecting an object just once, it might detect it multiple times. Non-max suppression is a way for you to make sure that your algorithm detects each object only once.


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[Assistant] Let's go through an example. Let's say you want to detect pedestrians, cars, and motorcycles in this image. You might place a grid over this, and this is a 19 by 19 grid.


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[Assistant] Now while technically this car has just one midpoint, so it should be assigned just to one grid cell,


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[Assistant] The car on the left also has just one midpoint so technically only one of those grid cells should predict that there is a car. In practice, you're running


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[Assistant] An object classification and localization algorithm for every one of these sprit cells. So it's quite possible that this sprit cell


[User] Please transcribe this text

[Assistant] might think that the center of the car is in it and so might this and so might this and for the car on the left as well maybe not only this box if this is a test image you've seen before not only that


[User] Please transcribe this text

[Assistant] Box might decide that things have found a car. Maybe this box and this box and maybe others as well will also think that they've found a car.


[User] Please transcribe this text

[Assistant] So let's step through an example of how non-max suppression will work.


[User] Please transcribe this text

[Assistant] So because you're running the, uhm, image classification and localization algorithm on every grid cell, on 361 grid cells, it's possible that many of them will raise their hand and say, my PC, my chance of thinking I have an object in it is large.


[User] Please transcribe this text

[Assistant] Rather than just having two of the grid cells out of the 19 squared or 361, think they've detected an object. So when you run your algorithm, you might end up with multiple detections of each object.


[User] Please transcribe this text

[Assistant] So what non-max suppression does is it cleans up these detections.


[User] Please transcribe this text

[Assistant] So that you end up with just one detection per car rather than multiple detections per car.


[User] Please transcribe this text

[Assistant] So concretely what it does is it first looks at the probabilities associated with each of these detections. Kind of the PCs, although there are some details you learn about in this week's programming exercises. Actually PC times C1 or C2 or C3, but for now let's just say it's PC.


[User] Please transcribe this text

[Assistant] Detection, so let's highlight that. I'm just saying, I found a car there.


[User] Please transcribe this text

[Assistant] Having done that, the non-max suppression part then looks at all of the remaining rectangles and all the ones with a high overlap, with a high IOU, with this one that you've just output.


[User] Please transcribe this text

[Assistant] We'll get suppressed. So those two rectangles with the 0.6 and the 0.7, both of those overlap a lot with the light blue rectangles, so those you're gonna suppress. We're gonna darken them to show that they're being suppressed.


[User] Please transcribe this text

[Assistant] Next, you then go through the remaining rectangles and find the one with the highest probability, the highest PC, which in this case is this one, it was 0.8. So let's commit to that and just say, oh I've detected a card there. And then the non-max suppression part is to then


[User] Please transcribe this text

[Assistant] Get rid of any other ones with a high ILU.


[User] Please transcribe this text

[Assistant] So now every rectangle has been either highlighted or darkened, and if you just get rid of the darkened rectangles, you're left with just the highlighted ones, and these are your two final predictions.


[User] Please transcribe this text

[Assistant] So this is non-max suppression, and non-max means that you're going to output your maximal probabilities, classifications, but suppress the close by ones that are non-maximal. So that ends the name non-max suppression. So let's go through the details of the algorithm.


[User] Please transcribe this text

[Assistant] Although for this example, I'm going to simplify it to say that you're only doing car detection.


[User] Please transcribe this text

[Assistant] So let me get rid of the C1, C2, C3 and pretend for this slide.


[User] Please transcribe this text

[Assistant] That each output for each of the 19 by 19, so for each of the 361, which is 19 squared, for each of the 361 positions, you get an output prediction of the following, which is the chance that there's an object, and then the bounding box. And if you have only one object, there's no, you know, C1, C2, C3 prediction.


[User] Please transcribe this text

[Assistant] The details of what happens here at multiple objects lead to the programming exercise which we'll work on towards the end of this week.


[User] Please transcribe this text

[Assistant] Now, to implement non-max suppression, the first thing you can do is discard all the boxes, or discard all the predictions, all the bounding boxes with PC less than or equal to some threshold, let's say 0.6. So we're going to say that unless you think there's at least a 0.6 chance that there's an object there, let's just get rid of it.


[User] Please transcribe this text

[Assistant] So this is cause all the low probability output boxes.


[User] Please transcribe this text

[Assistant] Together with a probability of that bounding box being a good one. So we're just going to discard all the bounding boxes that were assigned a low probability.


[User] Please transcribe this text

[Assistant] Next, while there are any remaining bounding boxes that you've not yet discarded or processed,


[User] Please transcribe this text

[Assistant] You're going to repeatedly pick the box with the highest probability, with the highest PC.


[User] Please transcribe this text

[Assistant] And then output that as a prediction. So this is a process on the previous slide of taking one of the bounding boxes and making it lighter in color. So you commit to outputting that as a prediction for that there's a car there.


[User] Please transcribe this text

[Assistant] Next, you then discard any remaining box, so any box that you have not output as a prediction and that was not previously discarded. So discard any remaining box with a high overlap, with a high IOU, with the box that you just output in the previous step.


[User] Please transcribe this text

[Assistant] So this second step in the wall loop was when on the previous slide you would darken any remaining bounding box that had a high overlap with the bounding box that we just made lighter, that we just highlighted.


[User] Please transcribe this text

[Assistant] And so you keep doing this while there's still any remaining boxes that you've not yet processed until


[User] Please transcribe this text

[Assistant] I've taken each of the boxes and either output it as a prediction or discarded it as having too high an overlap or too high an IOU with one of the boxes that you have just output as a predicted position for one of the detected objects.


[User] Please transcribe this text

[Assistant] I've described the algorithm using just a single object on this slide. If you actually try to detect three objects,


[User] Please transcribe this text

[Assistant] Say pedestrians, cars, and motorcycles, then the output vector will have three additional components, and it turns out the right thing to do is to independently carry out non-max suppression three times, one on each of the output classes.


[User] Please transcribe this text

[Assistant] But the details of that I'll leave to this week's programming exercise where you get to implement that yourself, where you get to implement non-max suppression yourself on multiple object classes.


[User] Please transcribe this text

[Assistant] So that's it for non-max oppression, and if you implement the object detection algorithm with this pride, you actually get pretty decent results.


[User] Please transcribe this text

[Assistant] But before wrapping up our discussion of the YOLO algorithm, there's just one last idea I want to share with you, which makes the algorithm work much better, which is the idea of using anchor boxes. Let's go on to the next video.


[User] Please transcribe this text

[Assistant] Hi again and welcome to the unique GUI web application development tutorial. In this video I'm going to show you how to make web applications using the GUI framework in Zalky.


[User] Please transcribe this text

[Assistant] So, what is a Unigy framework? Unigy is a framework that allows you to create web applications in Delphi.


[User] Please transcribe this text

[Assistant] Unity UI allows developers to focus on application business logic, rather than working on web application development details, such as working directly with HTML, JS or other web technologies.


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[Assistant] Unigui is a rare manner of framework that you can easily design by dropping and dragging the union confidence. And it looks like simple form designing.


[User] Please transcribe this text

[Assistant] So there are four steps to create a UniGUI powered web application. The first one is designing, compiling, debugging, and deploying.


[User] Please transcribe this text

[Assistant] New GY is based on Centa XJS. It is one of the industry's most advanced JavaScript libraries.


[User] Please transcribe this text

[Assistant] So, if you want to design the front and side, you can easily customize the JavaScript. Also, it supports many major deployment options. So, it's time to demo.


[User] Please transcribe this text

[Assistant] So now, I want to make Hello World application using Unity UI framework in Dolby. So click this, create a new project.


[User] Please transcribe this text

[Assistant] And now it generates all files for us and we have to confirm it. Yes. So here is our image UI form. You can design it.


[User] Please transcribe this text

[Assistant] And it's a main module, main DPR file.


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[Assistant] You can find this demo application in the installed folder. For example, C, Program Files, Msoft, Framework, UnityUI and the demos. And demo name is mdemo. So this demo covers all the features of this UnityUI framework. So here is the non-visual uni-components.


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[Assistant] In the users class, we have a uni-gy classes, uni-gy rec classes, and uni-gy form, and many many more.


[User] Please transcribe this text

[Assistant] Day, month, year. This now procedure gets to time.


[User] Please transcribe this text

[Assistant] Okay, and this is the server control panel form. It shows the many informations about the server, about this application, status, resources, street pool, and license. So we can select it, and delete, and we can go to the localhost


[User] Please transcribe this text

[Assistant] Components. Trigger it.


[User] Please transcribe this text

[Assistant] Hello and welcome back. This week you learn about object detection. This is one of the areas of computer vision that's just exploding and is working so much better than just a couple years ago. In order to build up to object detection, you first learn about object localization. Let's start by defining what that means.


[User] Please transcribe this text

[Assistant] You're already familiar with the image classification task where an algorithm looks at this picture and might be responsible for saying this is a car. So that was classification.


[User] Please transcribe this text

[Assistant] The problem you learn to build a neural network to address later in this video is classification with localization, which means not only do you have to label this as say a car,


[User] Please transcribe this text

[Assistant] But the algorithm also is responsible for putting a bounding box or drawing a red rectangle around the position of the car in the image.


[User] Please transcribe this text

[Assistant] So that's called the classification with localization problem. Where the term localization refers to figuring out where in the picture is the car you've detected. Later this week, you then learn about the detection problem, where now there might be multiple objects in the picture and you have to detect them all and, uhm, localize them all.


[User] Please transcribe this text

[Assistant] And if you're doing this for an autonomous driving application,


[User] Please transcribe this text

[Assistant] Problems usually have one object.


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[Assistant] Usually one big object in the middle of the image that you're trying to recognize or recognize and localize. In contrast, in the detection problem, there can be multiple objects. And in fact, maybe even multiple objects of different categories.


[User] Please transcribe this text

[Assistant] So the ideas you've learned about for image classification will be useful for classification with localization, and then the ideas you learn for localization will then turn out to be useful for detection.


[User] Please transcribe this text

[Assistant] So let's start by talking about classification with localization.


[User] Please transcribe this text

[Assistant] You're already familiar with the image classification problem in which you might input a picture into a confnet with multiple layers. So there's our confnet. And this results in, and this results in a vector of features that is fed to maybe a softmax unit that


[User] Please transcribe this text

[Assistant] So if you're building a self-driving car, maybe your object categories are the following where


[User] Please transcribe this text

[Assistant] You might have a pedestrian, or a car, or a motorcycle, or background. This means none of the above. So if there's no pedestrian, no car, no motorcycle, then you might have an output background. So if these are your classes, then you have a softmax with


[User] Please transcribe this text

[Assistant] Output units that output a bounding box. So in particular, you can have the neural network output four more numbers, and I'm going to call them bx, by, bh, and bw. And these four numbers parameterize the bounding box.


[User] Please transcribe this text

[Assistant] So in these videos, I'm going to use the notational convention that the upper left of the image


[User] Please transcribe this text

[Assistant] I'm going to denote as the coordinate zero zero and the lower right.


[User] Please transcribe this text

[Assistant] The midpoint, so that's the point bx comma by, as well as the height, that would be bh, as well as the width, bw of this bounding box.


[User] Please transcribe this text

[Assistant] So now, if your training set contains not just the object class label,


[User] Please transcribe this text

[Assistant] The ideal Bx might be about 0.5, because this is about halfway to the right of the image. By might be about 0.7, since that's about, you know, maybe 70% of the way down of the image. Bh.


[User] Please transcribe this text

[Assistant] BW might be about 0.3 because the height of this red square is about 30% of the overall height of the image. And BW might be about 0.4 let's say because the width of the red box is about 0.4 of the overall width of the entire image.


[User] Please transcribe this text

[Assistant] So let's formalize this a bit more in terms of how we define the target label y for this as a supervised learning task.


[User] Please transcribe this text

[Assistant] So just as a reminder, these are our four classes and the neural network now outputs those four numbers as well as a, um, class label.


[User] Please transcribe this text

[Assistant] Or maybe probabilities of the class labels. So let's define the target label y as follows. It's going to be a vector where the first component PC is going to be, is there an object? So if the object is, uhm,


[User] Please transcribe this text

[Assistant] So if the class is 1, 2, or 3, PC will be equal to 1. And if it's the background class, so if it's none of the objects you're trying to detect, then PC will be 0.


[User] Please transcribe this text

[Assistant] And PC, you can think of that as standing for the probability that there's a object, probability that one of the clauses you're trying to detect is there. So something other than the background clause. Next, if


[User] Please transcribe this text

[Assistant] There is an object, then you want it to output bx, by, bh, and bw.


[User] Please transcribe this text

[Assistant] or a motorcycle and remember in the problem we're addressing


[User] Please transcribe this text

[Assistant] We assume that your image has only one object, so at most one of these objects appears in the picture in this classification with localization problem.


[User] Please transcribe this text

[Assistant] So let's go through a couple of examples. If this is a training set image, so if that is x, then y will be


[User] Please transcribe this text

[Assistant] The first component PC will be equal to 1, because there is an object, then Bx, By, Bh, and Bw will specify


[User] Please transcribe this text

[Assistant] At most one of them should be equal to one. So that's if there is an object in the image. What if there's no object in the image? What if you have a training example where x is equal to that? In this case, PC would be equal to zero and


[User] Please transcribe this text

[Assistant] The rest of the elements of this will be don't cares. So I'm going to write question marks in all of them. So this is a don't care.


[User] Please transcribe this text

[Assistant] Because if there is no object in this image, then you don't care what bounding box the neural network outputs as well as which of the three objects, C1, C2, C3, it thinks it is. So given a set of label training examples, this is how you construct X


[User] Please transcribe this text

[Assistant] The input image as well as y, the class label, both for images where there is an object and for images where there is no object. And the set of these will then define your training set.


[User] Please transcribe this text

[Assistant] Finally, next let's describe the loss function.


[User] Please transcribe this text

[Assistant] You use to train the neural network. So the ground truth label was Y and the neural network outputs some Y hat. What should be the last B?


[User] Please transcribe this text

[Assistant] Well, if you're using squared error, then the loss can be


[User] Please transcribe this text

[Assistant] y2 hat minus y2 squared plus dot dot dot plus y8.


[User] Please transcribe this text

[Assistant] At minus y8 squared. Notice that, uh, y here has eight components. So that goes from


[User] Please transcribe this text

[Assistant] Some of the squares of the difference of the elements. And that's the loss if y1 is equal to 1.


[User] Please transcribe this text

[Assistant] So that's the case where there is an object. So y1 is equal to PC, right? So if PC is equal to 1, that is if there is an object in the image, then the loss can be the sum of squares over all the different elements. The other case is if


[User] Please transcribe this text

[Assistant] Y1 is equal to 0, so that's if uhm, this PC is equal to 0. In that case, the loss can be just Y1 hat minus


[User] Please transcribe this text

[Assistant] Why one squared? Because in that second case,


[User] Please transcribe this text

[Assistant] All the rest of the components are don't cares. And so all you care about is how accurately is the neural network outputting PC in that case. So just to recap, if y1 is equal to 1,


[User] Please transcribe this text

[Assistant] That's this case, then you can use squared error to penalize squared deviation from the, uh, predicted and the actual outputs for all eight components. Whereas if y1 is equal to zero, then


[User] Please transcribe this text

[Assistant] You know, the second to the eighth components I don't care, so all you care about is how accurately is your neural network estimating Y1, which is equal to, uhm, PC.


[User] Please transcribe this text

[Assistant] And just as a side comment for those of you that want to know all the details, I've used the squared error just to simplify the description here in practice.


[User] Please transcribe this text

[Assistant] You could use, uhm, you could probably use a log likelihood loss for the C1, C2, C3 to have a softmax output. One of those elements. Usually you can use squared error or something like squared error.


[User] Please transcribe this text

[Assistant] For the bounding box coordinates, and then for PC, you know, you could use something like the, uh, logistic regression loss. Although, even if you use squared error, it'll probably work okay.


[User] Please transcribe this text

[Assistant] So that's how you get a neural network to not just classify an object, but also to localize it.


[User] Please transcribe this text

[Assistant] The idea of having a neural network output a bunch of real numbers to tell you where things are in a picture turns out to be a very powerful idea.


[User] Please transcribe this text

[Assistant] In the next video, I want to share with you some other places where this idea of having a neural network output a set of real numbers almost as a regression toss, uh, can be very powerfully used elsewhere in computer vision as well. So let's go on to the next video.


[User] Please transcribe this text

[Assistant] In this video you learn about a function called intersection over union. And this will be used both for evaluating your object detection algorithm as well as in the next video using it to add another component to your object detection algorithm to make it work even better.


[User] Please transcribe this text

[Assistant] Let's get started. In the object detection task, you're expected to localize the object as well. So if that's the ground truth bounding box, and if your algorithm outputs this bounding box in purple, is this a good outcome or a bad one? So what the intersection over union function does, or iou does, is it computes


[User] Please transcribe this text

[Assistant] The intersection over union of these two bounding boxes. So


[User] Please transcribe this text

[Assistant] The union of these two bounding boxes is this area, is really the area that is, you know, contained in either bounding boxes, whereas the intersection is this smaller region here.


[User] Please transcribe this text

[Assistant] And by convention, a lot of computer vision tasks will judge that the answer is correct if the IOU is greater than 0.5.


[User] Please transcribe this text

[Assistant] And, uh, if the predicted and the ground truth bounding boxes overlapped perfectly, the IOU would be 1.


[User] Please transcribe this text

[Assistant] Because the intersection would equal to the union, but in general, so long as the IOU is greater than or equal to 0.5, then, you know, the answer will look okay. It will look pretty decent. And by convention, very often 0.5 is used as a threshold to judge as whether the predicted bounding box is correct or not.


[User] Please transcribe this text

[Assistant] This is just a convention. If you want to be more stringent, you can judge an answer as correct only if the IOU is greater than or equal to 0.6 or some other number.


[User] Please transcribe this text

[Assistant] But the higher the IOUs, the more accurate the bounding box.


[User] Please transcribe this text

[Assistant] And so this is one way to map localization to accuracy where you just count up the number of times an algorithm correctly detects and localizes an object where you could use a definition like this of whether or not the object is correctly localized.


[User] Please transcribe this text

[Assistant] And again, 0.5 is just a human chosen convention. Uh, there's no physically deep theoretical reason for it. You can also choose some other threshold like 0.6 if you want to be more stringent.


[User] Please transcribe this text

[Assistant] Uhm, I sometimes see people use more stringent criteria like 0.6 or maybe 0.7. I rarely see people drop the threshold below 0.5.


[User] Please transcribe this text

[Assistant] Now, we've motivated the definition of IOU as a way to evaluate whether or not your object localization algorithm is accurate or not. But more generally, IOU is a measure of the overlap between two bounding boxes.


[User] Please transcribe this text

[Assistant] Where if you have two boxes, you can compute their intersection, compute their union, and take the ratio of the two areas.


[User] Please transcribe this text

[Assistant] And so this is also a way of measuring how similar two boxes are to each other. And we'll see this used again this way in the next video when we talk about non-max suppression.


[User] Please transcribe this text

[Assistant] So that's it for IOU or Intersection Over Union. Uh, not to be confused with the promissory note concept in IOU, where if you lend someone money, they write you a note that says, oh IOU this much money, so that's also called an IOU.


[User] Please transcribe this text

[Assistant] Totally different concept but maybe it's cool that, you know, these two names, these two things have a similar name.


[User] Please transcribe this text

[Assistant] Uhm, so now, armed with this definition of IOU, intersection of a union, in the next video, I want to discuss with you non-max suppression, which is a tool you can use to make the outputs of YOLO work even better. So let's go on to the next video.


[User] Please transcribe this text

[Assistant] And here, like this one. But, we can use the ID features. Like, we can undo it, here. So, you can open the context menu in the editor, and you can click this format source or the Ctrl plus ID keys on the keyboard.


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[Assistant] And here we got practice to demo application, and we are using the generics.collections in the user's clouds. And we are declaring the tnumbered list.


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[Assistant] And you can remove by its index here, 1, the first element, and intlist.insert. You can show the 1 here, this is index, and this 10 for setting up the new value. And you can also sort this list here.


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[Assistant] It's strength lies in the fact that it is a generic type and that both the key and the value can be of any type at all. For instance, you could have a dictionary that had a T-memo as the key and T-button as the value. So here we are declaring the T-people dictionary.


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[Assistant] So in the process people, we have declared the people dictionary. It's from tpeople dictionary. And here, creating this people dictionary on the memory. And you can add data like this. This is string. And next, integer.


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[Assistant] So here is the event log. We got debug output onCreateEvents.


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[Assistant] In this one. And here, add an output for a mouse move. And then click this.


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[Assistant] Today we are supplying this product, uh, not only for sportswear, but for outerwear, for home textiles, for ladies' apparels. So all types of applications are possible because the quality of this recycled yarn


[User] Please transcribe this text

[Assistant] World so high, like a diamond in the sky. Twinkle, twinkle little star, how I wonder what you are.


[User] Please transcribe this text

[Assistant] All the wheels on the bus go round and round, round and round, round and round. All the wheels on the bus go round and round, all through the town.


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[Assistant] Q R S T U V W X Y and Z Now I know my ABC's Next time won't you sing with me


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[Assistant] Okay, but now I want to move to the next topic, which is the topic called the Capital Asset Pricing Model.


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[Assistant] Uh, the theory hasn't worked out as well as people thought.


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[Assistant] Uh, in recent times, but it's quite a great


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[Assistant] Achievement, and a lot of it was done here at Yale, so I want to explain it to you. So, you see we have a problem so far. If everybody's trying to hedge, that means everybody's trying to get a completely, you know, riskless payoff.


[User] Please transcribe this text

[Assistant] It's impossible, because I mean, there's real risk in the economy. And so, and what do we mean by real risk? Well, something in one state is just gonna be bad for the whole economy compared to another state. Maybe we'll run out of oil or something like that. It's impossible that everybody can consume the same thing in every state.


[User] Please transcribe this text

[Assistant] So, it's impossible that everybody can perfectly hedge. But everybody wants to perfectly hedge.


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[Assistant] So, what has to happen? What gives, how does the theory have to change? Well, the theory's gonna change in a...


[User] Please transcribe this text

[Assistant] What's going to happen is everybody is going to try and hedge as much as they can by diversifying.


[User] Please transcribe this text

[Assistant] But because there's some real risk in the economy in some states,


[User] Please transcribe this text

[Assistant] The consequence of that is if you're going to buy an asset that pays something that's


[User] Please transcribe this text

[Assistant] You're gonna pay the discounted expected return of the asset. But if you're gonna buy an asset that's risky,


[User] Please transcribe this text

[Assistant] You're gonna need a higher rate of return. So the price will be less.


[User] Please transcribe this text

[Assistant] So Shakespeare, remember, said exactly that. When the play begins with Antonio looking melancholy, his interlocutor says, so Lario or somebody asks him whether he's worried about his businesses. He says, no, I've got a different ship.


[User] Please transcribe this text

[Assistant] Every ship's on a different ocean, so I'm diversified, I'm not that worried.


[User] Please transcribe this text

[Assistant] So Shakespeare knows about diversification and that's what everybody should do. But then when it comes time to pick the casket.


[User] Please transcribe this text

[Assistant] The uh, but they sign a contract that whoever picks the wrong casket not only doesn't get Portia, he can never marry anyone in the future.


[User] Please transcribe this text

[Assistant] Uh, expected payoff for the expected return, that is the payoff per dollar put into it, looks higher to compensate you for the risk.


[User] Please transcribe this text

[Assistant] So Shakespeare almost had the whole story. What's missing from Shakespeare? Well, what is the definition of risk is missing from Shakespeare?


[User] Please transcribe this text

[Assistant] And how should that affect the price of things, and how does that affect all the analysis we've done so far? Okay, so that's the topic of the next couple lectures. So, the first person to confront this problem in a, in


[User] Please transcribe this text

[Assistant] Propose a solution, a mathematical solution with the mathematician Bernoulli and his brother.


[User] Please transcribe this text

[Assistant] Uh, and one of the brothers went off to St. Petersburg, where he ended up dying shortly afterwards, but he invented, uh, he noticed the following puzzle.


[User] Please transcribe this text

[Assistant] Suppose I, and some of you have heard this, it's called the St. Petersburg Paradox.


[User] Please transcribe this text

[Assistant] So suppose I offer you a bet. I say, uh, I'm gonna flip a coin.


[User] Please transcribe this text

[Assistant] And I keep flipping the coin until it comes up pale.


[User] Please transcribe this text

[Assistant] I count how many coin flips I've had, I've counted until you get tails, and if that's n flips, you get 2 to the n dollars.


[User] Please transcribe this text

[Assistant] So if you flip it one time and it comes up tails right away, which is probability a half, you get two dollars.


[User] Please transcribe this text

[Assistant] If I flip it two times and it gets heads and then tails, okay, that's with probability a quarter, you get


[User] Please transcribe this text

[Assistant] If I flip it three times and I get heads, heads, tails, the odds of that are a half times a half times a half, which is an ace.


[User] Please transcribe this text

[Assistant] But then you'll get 2 to the 3 dollars, okay, so 4 plus 8 plus, you know, 1 over 2 to the n times 2 to the n plus dot dot dot.


[User] Please transcribe this text

[Assistant] So Bernoulli, the one who died, uhm,


[User] Please transcribe this text

[Assistant] So according to what we've said so far, you should pay infinite amount of dollars for it.