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[Assistant] But for biodegradable plastic, paper, or cotton bags, the number of times you'd need to reuse them is well beyond how long you would expect an individual bag to last. Now, only the Danish report calculated the total impact like this, so we don't yet have multiple studies to support those numbers. Still, just based on that,


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[Assistant] It might seem like plastic comes out ahead. And the plastic industry is happy to use this logic in these comparison studies to lobby against the regulation of single-use plastics. But there is one more key variable.


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[Assistant] Disposal. Here is plastic's Achilles heel. There's no good way to dispose of it.


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[Assistant] So if you add in litter and impacts on marine ecosystems, single-use plastics look a lot less green. It's hard to get good data on what fraction of plastic bags are recycled, but we know it is low, possibly around 1 to 3%. Many recycling programs don't accept them for the simple reason that they get


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[Assistant] They can become wrapped around creatures mistaken for food and eaten, or even spread invasive species that hitch a ride. And this is one area that life cycle assessment studies fall short in. They don't have a way of comparing the effects of litter on ecosystems. Regardless,


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[Assistant] New materials like biodegradable or compostable bags are supposed to solve this problem. But while a 2019 study found that these are better than traditional plastics, after three years,


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[Assistant] None of the bags tested broke down in all environments. Paper bags are biodegradable, so the impact of litter is low. And they're recyclable, but left to break down in a landfill, they release methane.


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[Assistant] For the heavier, reusable plastic and cotton bags, disposal should be a smaller part of the overall footprint, since hopefully they've been reused many times. Both can be recycled, but that doesn't mean that they always are. For example, only around 15% of textiles, a broad category that includes cotton bags, end up recycled.


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[Assistant] Is? It's complicated! The best material depends on many factors, including your individual habits, like how many times you reuse each type of bag and how you dispose of your bags. Overall, making single-use plastic bags has a relatively low environmental impact.


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[Assistant] But waste is a massive problem with no good solution. The best option for the end of a plastic bag's life is to reuse it as a trash bag. Presumably, you would be using something to contain the trash anyway, and if nothing else,


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[Assistant] The bag is a lot less likely to float away if it's weighed down by all the stuff inside it. Meanwhile, manufacturing paper or biodegradable plastic has higher impacts, but these materials reduce the problem.


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[Assistant] And heavier, reusable plastic bags are a great option if you reuse them enough. Cotton tote bags have by far the biggest environmental impact. They look very green when you've got them on your shoulder. Turns out,


[User] Please transcribe this text

[Assistant] That's kind of a lie. They need to be reused hundreds of times to counteract their climate footprint, and possibly thousands if you consider multiple environmental impacts. So we're not saying plastic bags are good.


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[Assistant] They're not. But it is important to remember that the alternatives have an impact, too. It's not worth going out to buy a snazzy new reusable product if you already have one.


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[Assistant] And reuse them as many times as possible. And when you cannot use a bag anymore, do whatever you can to make sure it does not become litter. It's also worth keeping in mind that despite all of the attention grocery bags get, they are only a very small part of our impact on this planet. But looking at the entire life cycle of a product can be a useful way to analyze nearly any aspect of our lives.


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[Assistant] Exploring questions like these. Because often, the things that seem the most simple are actually really nuanced and fascinating. And we would not be able to do things like this


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[Assistant] Without the support of our Patreon community. So to all of our patrons, thank you for helping us make videos like this. If you're not a patron but want to learn more about supporting free science education on the internet, you can head on over to patreon.com slash SciShow.


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[Assistant] In this video, I'd like to show you the hypothesis representation. That is, what is the function we're going to use to represent our hypothesis when we have a classification problem.


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[Assistant] Earlier we said that we would like our classifier


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[Assistant] To output values that are between 0 and 1. So we like to come up with a hypothesis that satisfies this property, that its predictions are maybe between 0 and 1.


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[Assistant] When we were using linear regression, this was the form of a hypothesis where h of x is theta transpose x.


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[Assistant] For logistic regression, I'm going to modify this a little bit and make the hypothesis g of theta transpose x, where I'm going to define the function g


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[Assistant] As follows, g of z, if z is a real number, is equal to 1 over 1 plus e to the negative z.


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[Assistant] Logistic function, and the term logistic function, that's what gives rise to the name logistic regression.


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[Assistant] And by the way, the terms sigmoid function and logistic function are basically synonyms and mean the same thing. So the two terms are basically interchangeable and either term can be used to refer to this function g.


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[Assistant] And if we take these two equations and put them together, then here's just an alternative way.


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[Assistant] I'm writing out the form of my hypothesis. I'm saying that h of x is 1 over 1 plus e to the negative


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[Assistant] Theta transpose x and all I've done is I've taken this variable z, z here is a real number and plugged in theta transpose x. So I end up with, you know, theta transpose x in place of z there.


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[Assistant] The sigmoid function, g of z, also called the logistic function, it looks like this. It starts off near zero.


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[Assistant] And then it rises until it crosses 0.5 at the origin.


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[Assistant] And then it flattens out again like so. So that's what the sigmoid function looks like.


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[Assistant] And you notice that the sigmoid function, well, it asymptotes at 1.


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[Assistant] And it asymptotes at zero as a z, I guess the horizontal axis of z. As z goes to minus infinity, g of z approaches zero. And as g of z approaches infinity, g of z approaches one.


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[Assistant] And so because g of z outputs values that are, you know, between 0 and 1, we also have that h of x must be between 0 and 1. Finally, given this hypothesis representation,


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[Assistant] What we need to do, as before, is fit the parameters theta to our data.


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[Assistant] So given a training set, we need to pick a value for the parameters theta, and this hypothesis will then let us make predictions.


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[Assistant] We'll talk about a learning algorithm later for fitting the parameters later.


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[Assistant] But first let's talk a bit about the interpretation of this model.


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[Assistant] Here's how I'm going to interpret the output of my hypothesis H of X.


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[Assistant] When my hypothesis outputs some number, I am going to treat that number as the estimated probability that y is equal to 1 on a new input example x. Here's what I mean. Here's an example.


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[Assistant] Let's say we're using the tumor classification example. So we may have a feature vector x, which is this x zero equals one as always, and then our one feature is the size of the tumor.


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[Assistant] Suppose I have a patient come in and, you know, they have some tumor size and I feed their feature vector x into my hypothesis, and suppose my hypothesis outputs the number 0.7.


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[Assistant] I'm going to interpret my hypothesis as follows. I'm going to say that this hypothesis is telling me that for a patient with features x, the probability that y equals 1 is 0.7. In other words, I'm going to tell my patient


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[Assistant] That tumor sadly has a 70% chance or a 0.7% chance of being malignant.


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[Assistant] To write this out slightly more formally or to write this out in math, I'm going to interpret my hypothesis output as P of y equals 1 given x parameterized by theta.


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[Assistant] So for those of you that are familiar with probability, this equation may make sense. If you're a little less familiar with probability, here's how I read this expression.


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[Assistant] This is the probability that y is equal to 1, given x, so given that my patient has, you know, features x, or given my patient has a particular tumor size represented by my features x, and this probability is parameterized by theta.


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[Assistant] So I'm basically going to count on my hypothesis to give me estimates of the probability that y is equal to 1.


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[Assistant] Now, since this is a classification task, we know that y must be either 0


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[Assistant] All one, right? Those are the only two values that Y could possibly take on either in the training set or for new patients that may walk into my office or into the doctor's office in the future.


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[Assistant] So given h of x, we can therefore compute the probability that y is equal to 0 as well. Concretely, because y must be either 0 or 1,


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[Assistant] We know that the probability of y equals 0 plus the probability of y equals 1 must add up to 1.


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[Assistant] This first equation looks a little bit more complicated, but it's basically saying that probability of y equals zero for a particular patient with features x, and, you know, given our parameters data,


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[Assistant] Um, plus the probability of y equals one for that same patient with features x and give our parameters data must add up to one.


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[Assistant] If this equation looks a little bit complicated, feel free to mentally imagine it without that x and theta.


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[Assistant] And this is just saying that the probability of y equals zero plus the probability of y equals one must be equal to one. And we know this to be true because y has to be either zero or one, and so the chance of y being equal to zero plus the chance that y is one, you know, those two must add up to one.


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[Assistant] And move it to the right hand side, then you end up with this equation. It says probably y equals zero, it's one minus probably y equals one.


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[Assistant] And thus if our hypothesis, if h of x gives us that term, you can therefore quite simply compute the probability or compute the estimated probability that y is equal to zero as well.


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[Assistant] So you now know what the hypothesis representation is for logistic regression. And we've seen what the mathematical formula is defining the hypothesis for logistic regression.


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[Assistant] In the next video, I'd like to try to give you a better intuition about what the hypothesis function looks like. And I want to tell you about something called the decision boundary, and we'll look at some visualizations together to try to get a better sense of what this hypothesis function of logistic regression really looks like.


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[Assistant] Two people possess a secret so valuable, so powerful, they have to defend it at all costs.


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[Assistant] They only had one chance, and their chance was to fight back.


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[Assistant] Okay, you want to play rough? Say hello to my little friend! With a little help from the governor.


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[Assistant] Nothing will prevent them from doing their job. Double the action! Get down! Triple the excitement! Get down again! This summer, nothing will stand in their way. I'm gonna make him an offer he can't refuse. Two hosts, one podcast. EnglishPod, coming to a theater near you.


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[Assistant] The capital asset pricing model.


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[Assistant] Uh, it's a model of the optimal portfolio. It asserts that all investors will hold the optimal portfolio.


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[Assistant] So anyway, I showed you last time a scatter diagram which had on the horizontal axis the return on the stock market and on the vertical axis the return on Apple computer. And there was a scatter of points, one for each year, the return on the market and the return on Apple for that year.


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[Assistant] Uh, and I had fitted a line through that scatter of points. The slope of the line is called beta. The idea here is that


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[Assistant] Individuals should diversify. They should hold many different eggs in their basket. But diversification is difficult for individual investors.


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[Assistant] Uh, partly because if you're a small investor, you'd have to buy fractional shares of each company. And, you know, the stockbrokers prefer that you do what's called round lots of a hundred shares.


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[Assistant] So you just can't do it. You're too small to diversify. So you need some company to help you diversify your portfolio.


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[Assistant] So the idea has been, going back many decades, that people need investment funds to manage their portfolio for them, and the investment funds can diversify optimally for them.


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[Assistant] Later they became in a different form called a mutual fund.


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[Assistant] Uh, the, the first mutual fund is Massachusetts Investment Trust, MIT, not the Institute, uh, in the 1920s, but it, uh, it didn't, uh, they didn't really take off until


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[Assistant] After the 1940s. So a mutual fund or management company invests


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[Assistant] In your behalf, uh, in assets. And it's mutual in that it doesn't skim off profits to a class of stockholders. It's divided up equally among all the people who invest in the mutual fund.


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[Assistant] I, now the question of whether we're really talking about complete diversification or not, often when we talk about the capital asset pricing model, or I should say usually,


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[Assistant] It is assumed that we're diversifying across all stocks and maybe all stocks and all bonds. But in fact, if you wanted to be completely diversified, you'd want to include other assets like real estate or commodities like oil as well.


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[Assistant] I put this up because I had to take an exam to get licensed as a stockbroker at one point in my career. Because I had a company. And it turned out I had to be licensed. So I took the exam to become a stockbroker.


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[Assistant] I never was a stockbroker in my life. And the exam study materials, this is a series 7 exam that some of you might end up taking if you go into finance.


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[Assistant] They talked about classifying all the different investments that someone might make in terms of risk. So there's low risk, moderate risk, moderate risk, high risk,


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[Assistant] Now they have an image of mountain climbers climbing to the top. Now they didn't say what, I had to memorize this for the exam. Something didn't bother me about it though. They didn't say what you do with this picture of a pyramid.


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[Assistant] So it sounds like, looking at the picture, like, uh, we are supposed to be climbing up to the most speculative investments. Uh, I don't know. Uh, but what I thought is, uh, there's nothing wrong with this diagram, but somehow it's misleading. What, what CAPM says,


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[Assistant] Doesn't matter what your risk is, you want to hold all of these.


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[Assistant] It'll average out to be the best for you. So, speculative. Art, gems, precious metals, options, commodities, venture capital. I want all of them. Okay? Do you want these too? Yes, I want all of them.


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[Assistant] Uh, it's very simple. It's not like going to a candy store. You probably just buy one piece of candy. You walk into the candy store and say, give me one of everything. Uh, that's what you should do.


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[Assistant] Jeremy Siegel, who is an old friend of mine at the Wharton School, has just come out with the fifth edition of his book, Stocks for the Long Run.


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[Assistant] Uh, and he calculates the average return on the stock market in the United States from 1802 to 2012. That's 210 years of data. It's a lot of data.


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[Assistant] Uh, and he finds that, um, correcting for inflation


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[Assistant] Uh, the real inflation corrected return on average for those 200 years was 6.6% a year.


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[Assistant] Uh, so the equity premium, equity means stocks.


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[Assistant] The premium of stocks over short-term saving vehicles on average for 200 years was 3.9%.


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[Assistant] Uh, so then he poses it as a puzzle in the beginning of his book. How can that be? That's 200 years is a long time.


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[Assistant] I'm thinking everyone, this is your first thought, should invest in the stock market.


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[Assistant] Why does anyone invest in, uh, short-term governments? Uh, so this is called the equity premium puzzle. How can it be that one investment has done so much better overall for 200 years compared to another?


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[Assistant] Uh, and that's what we're going to try to understand with the capital asset pricing model here. It's not just for the US, but not as dramatically. Uh, Will Getzman said that to some extent the US equity premium is a, uh,


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[Assistant] The United States is the most successful capitalist country in the world, you might argue. Someone might try to argue otherwise, but if we're not, we're pretty close to it.


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[Assistant] So, looking at the success of stock market investments in the United States is misleading.


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[Assistant] So you might say, let's look at another country. How about Russia? Alright? Well, let's think. Whatever happened in Russia, if we're taking it along, from 1802? You know, I kind of remember there was something called the Bolshevik Revolution. So basically, it was wiped out. You didn't get anything. So, uh,


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[Assistant] They're not uniformly a good example, but at least in the US, it seems like, now we may be making a fallacy in assuming that this book is God's law, that stocks outperform other investments, but it seems like they have been.


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[Assistant] Right. You're getting at a basic issue, is what do we know about the future?


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[Assistant] And does the past have any indication of the future?


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[Assistant] Big question. So, let me give you an example.


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[Assistant] Utilities stocks, that's electric companies, gas companies, they, they, they, every month they, they keep the lights on. They've been doing this for a long time. So, uh, they're boring stocks.


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[Assistant] And they'd hardly ever have gone bankrupt. So people think those are safe stocks with a low beta or a low idiosyncratic variance. And maybe they don't pay the highest return.


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[Assistant] So it almost seems reasonable, doesn't it, that they're going to continue? What's exciting about them, you know?


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[Assistant] But on the other hand, if you look at the history of, I'm just bringing up utilities,


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[Assistant] They weren't always boring, particularly the 1920s when the world was becoming electrified and electricity


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[Assistant] This was obviously lit by gas when it was built, not by electricity.


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[Assistant] Once the electric- the electricity is so much brighter and impressive so, uh, people were excited about it. So in 1929 the sector that grew the most and crashed was the utility sector. So that means you can't necessarily trust past


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[Assistant] I think that it's kind of halfway. You can sort of trust it. If you know other, if you know a reason to think otherwise, then you, you wouldn't.


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[Assistant] But when you get to other things like Facebook or Google or whatever, or Alphabet, what do you think about their future return?


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[Assistant] Is that predicted by their past return? And see, now we're, who knows, right? It's, uh, it's, it's changing. Everything's changing too fast.


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[Assistant] I'm afraid I can't help you right now. I'm getting ready for a very important meeting.


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[Assistant] Ten? Of course. That's ten dollars, please. Here you are.


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[Assistant] Can I help you with all that? No thanks, I have this cart.


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[Assistant] Ten bags. That's a lot of salt.


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[Assistant] It is. But why do you need ten bags?


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[Assistant] But we want our salt. And we want it now.


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[Assistant] What are we going to do? That's your problem. It's six o'clock. Time to close the store. I'm going home.


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[Assistant] There's a lot of salt in the world. Enough for everybody. Goodbye.


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[Assistant] Mary, please. There's something out there.


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[Assistant] Ah! You! James! James Heston! But you! You're dead!


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[Assistant] Beth was a good woman. And a good sister to me. I said to her, don't go with Keach. Think of James. He's dead now.


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[Assistant] No. Keach can kill me with one hand. He's big. He always has a knife in his pocket. Last year he killed a man with that knife. I'm afraid of him, James.


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[Assistant] No. Oh. Yes, a little. You're a ghost.


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[Assistant] I'm going mad. Why does my hand throw a book when I don't want to? Can all dead people do this? Can they get into man's head so he moves a chair or throws a book?


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[Assistant] But how? How can I get the money from Keach?


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[Assistant] Stop laughing. Be quiet, all of you. Sit down, Mary. Thank you. Yes, James Heston is dead. And yes, James Heston spoke to me. I want James Heston here. Now.


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[Assistant] He can tell you. He is ill. He's mad. Let's listen to him. Yes, we can listen to him. Be quiet. Call James Heston.


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[Assistant] James Heston, is it you? Did you speak to Richard Little? Yes. What did you


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[Assistant] It was Kate! Kate took the money!


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[Assistant] Can I hear something? Mary? Is that you? Oh no, it's not James again. James, is that you?


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[Assistant] Yes, I'm dead. And you killed me. But I'm not going away. I'm staying here in prison with you.


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[Assistant] You can't hit me now. You can't hit a ghost. And you can't kill me again. But we can talk. We have time for that. We have all day. And you can do that all day too. All day? All the time? Yes. Now throw the book across the room again. And again.


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[Assistant] Are all my days going to be like this? Your days, yes. And for your nights, I have a friend here.


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[Assistant] The salt and vinegar chips scare the hell out of me. Got no idea how to use those in a dessert. Awesome guys, good luck.


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[Assistant] With the mystery box, I really just want to use one or two of the ingredients that really speak to me. Really freaking out a bit.


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[Assistant] As soon as I see the passion fruits, I really wanna make a passion fruit curd. It's got bucket loads of flavour, and I know that if I can get these elements right, it's gonna be bang for buck.


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[Assistant] Yeah, dessert is not my strong point. So what is this? The dish is, uh, meringue kisses with passion fruit and yuzu curd. It's very simple, but that, that, it's something that I've been sort of, uh, trying out and then I'm confident with. Well, when it's simple, you have to nail those simple things.


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[Assistant] I just want to get tasted today. To win would just be an added bonus, but a tasting would just sort of cement me in that I can cook desserts and just give me a good positivity about myself. Just keep it really simple, stupid.


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[Assistant] It's, uh, meringue kisses with passion fruit and yuzu curd. Is it enough? If I can nail the elements and simple flavours, then I think, uh, yeaah. And will you nail them? I am nailing them. Okay, you can nail it, Gary. Puts him under pressure. Have another chips. Yeah, thanks guys.


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[Assistant] I'm really happy with how the meringue looks. It's stiff peaked, it's fluffy, it's light, no granules of sugar. The combination of the meringue and the passion fruit yuzu curd are just gonna work like a match made in heaven.


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[Assistant] Being a builder, handling delicate little meringues, it's not something that I'm used to. I'm really worried that I'm not doing enough.


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[Assistant] Five dishes are getting tasted and the top two are going straight through to immunity.


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[Assistant] I'm just completely blindsided by getting called up. I'm really hoping that the judges have just appreciated the simplicity of my dish.


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[Assistant] I can't wipe the smile off my face. I'm giving them something that they really enjoy. Can't ask for anything more.


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[Assistant] Sleep now my darling. Scene 1. Jenny must stay at home. It is a hot summer day.


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[Assistant] Jenny and Gilbert Lawson are having breakfast at a table in their garden. Gilbert is reading a book.


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[Assistant] Mmmm, this is good bread. Did you make it?


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[Assistant] Yes. I watched my new friend again last week.


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[Assistant] But now I have this new film, so I must go to America for six weeks.


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[Assistant] Perhaps next time. Would you like that? Perhaps you can be in the next film.


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[Assistant] Yes, this bread is very good.


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[Assistant] Love, I must go now. I'm going to be late for the plane. I love you, Jenny.


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[Assistant] Scene three. Jenny learns about Gilbert. There are four people at the check-in. Woman one, woman two, a man, and Jenny's father. They are waiting. A British Airways man is looking at father's plane ticket. Jenny runs in.


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[Assistant] Ah, Mrs Lawson, we phoned you at home. There was no answer. Mrs Lawson, I'm sorry.


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[Assistant] But Mr Lawson's plane crashed in the sea. He's dead.


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[Assistant] Scene 4. Jenny understands everything.


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[Assistant] Jenny's father and mother, and Jenny, are all sitting at a table


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[Assistant] Why is snow white? Coz it applies fairness cream. No.


[User] Please transcribe this text

[Assistant] Sunlight or white light is a combination of all visible colors of light. When light falls on an object, it may absorb some colors of light and reflect the remaining colors. The colors which are reflected by an object make up its color.


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[Assistant] For example, when light falls on an apple, it absorbs all other colors except red. Apple reflects red color, making it appear red.


[User] Please transcribe this text

[Assistant] Now, snow does not absorb any colors of light and reflects all of them equally. As the combination of all colors of light is white light, snow appears white to us.


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[Assistant] I know our choux buns look perfect, but I have no idea what they're going to think of the flavour combination. Really happy with all the elements, we just need to get them on the plate now.


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[Assistant] Another layer of green, another layer of brown. I hope you oiled that well. I wanna do layers of the different flavours. Alright, let's go, let's go, let's go, brown, brown, brown. So I start with the chocolate coffee and cardamom, the next layer is pistachio and so on. Did oil it. Let's hope I oiled it well enough.


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[Assistant] I'm really proud of the flavours that we've got into these shoe buns today, but I hope the flavours also work together and the judges are going to love it.


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[Assistant] Yeah, really pleased with the shoe. Chloe did an amazing job. We knew from the beginning that we were going to be pushing it with a crackling, but we really wanted those round, perfect shoe buns, so really glad we got it on the plate.


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[Assistant] I've watched MasterChef since day one, so to have Adriano Zumbo love our croquembouche is just, it's the best thrill. There's really no words for it.


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[Assistant] We won the Crockerbush challenge. I'm so excited. That was the best cook. I'm just beyond happy.


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[Assistant] Can't believe Catherine Sadworth is here today. She's an amazing cake decorator. I'm really excited to see what the pressure test is.


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[Assistant] I'm really worried about Jess's sponge because she dropped a little bit of yoke in it and uhm, I know from my experience it's really hard to get that yoke out.


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[Assistant] Hello English learners, welcome back to EnglishPod, my name is Marco. And I'm Erica. And today we're bringing you part four of our romantic series called I'm Sorry I Love You.


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[Assistant] We got a lot of drama and we got a lot of useful language.


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[Assistant] Okay. Exactly. So, in our dialogue today, Veronica and her boyfriend are on a break.


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[Assistant] Take a break. Okay, let's take a break. Okay, so let's listen to our dialogue, and it's gonna be a little bit fast, and the girl I think she's crying, so it'll be a little bit difficult to understand.


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[Assistant] So, but not so much as an on the street with all the neighbors coming out to see me.


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[Assistant] Alright, let's take a look at the language that we saw in our dialogue on Language Takeaway.


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[Assistant] Alright, so let's take a look at our first word, seeing someone.


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[Assistant] But not really, it's more of a casual thing, it's not very exclusive.


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[Assistant] Okay. Yeah, see this is the difficult thing about seeing someone is that for some people it means it's really serious while for other people it means it's more casual.


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[Assistant] Okay, so, if you're cheating on someone,


[User] Please transcribe this text

[Assistant] Exactly. So, if I say, she cheated on me.


[User] Please transcribe this text

[Assistant] That means that my girlfriend kissed or had sex with another guy.


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[Assistant] Okay, let's take a look at our next word. Messed this up. Messed this up. Messed this up.


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[Assistant] Exactly. Why don't we listen to some examples and then we can come back and talk some more.


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[Assistant] Alright, let's take a look at our next word. Immature.


[User] Please transcribe this text

[Assistant] Immature. So when someone is immature,


[User] Please transcribe this text

[Assistant] Right. It's normal for children to be immature.


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[Assistant] Alright, so, immature. Now let's take a look at our next word, selfish.


[User] Please transcribe this text

[Assistant] So it's not a good thing to be mature or selfish. Exactly.


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[Assistant] Okay, so I think it's time for us to listen to our dialogue again. We're gonna slow it down a little bit.


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[Assistant] Let's take a look at some of the phrases she used in Fluency Builder.


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[Assistant] Okay, so if somebody is worried or somebody is crying, you can say, ah, don't worry, everything is going to work out just fine.


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[Assistant] Okay. Okay, let's look at the next one. Pull yourself together.


[User] Please transcribe this text

[Assistant] Okay, just like calm down. Yeah, yeah. Get organized. Yeah, yeah, yeah. With your ideas and your thoughts.


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[Assistant] Alright, and the last phrase that we saw. It's going to be alright. It's going to be alright. It's going to be alright. It's going to be alright. So it's going to be alright means everything is going to be okay.


[User] Please transcribe this text

[Assistant] Okay, exactly, very useful language, so let's listen to some more examples.


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[Assistant] Okay, great examples and I think it's clear now. So let's listen to our dialogue again and then we'll come back and talk some more.


[User] Please transcribe this text

[Assistant] Okay, yeaah, I really like this dialogue, it's so romantic. Yeaah. It's drama, but at the same time romantic.


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[Assistant] Okay, so we're out of time for today. I hope you guys had fun, and we'll see you next time. Until then, it's... Goodbye!


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[Assistant] They'll have to deliver world-class cuisine.


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[Assistant] Lift your right hand up, put your hand on a cloth. Come on.


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[Assistant] But I think that's a good start. Prawns are fantastic, they're versatile.


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[Assistant] It's so delicious, it's so authentic. And I'm so happy for you Jess.


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[Assistant] I'm probably the easiest person to cook Greek for because I go against all the...


[User] Please transcribe this text

[Assistant] So disjointed and there's a few problems here. That's not, not a beautiful pita bread, a flatbread. A tzatziki that's, you know, the original tzatziki was a salad.


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[Assistant] What an awesome round the world ticket it was for the three of us. Prawns were the hero ingredient and you guys gave us some really delicious, spectacular, yummy dishes. First the good news. If I call your name, you are safe. Sarah. Gina.


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[Assistant] Although we wish you loaded your prawns with more fresh and delicate chervil. Ben we wished you had peeled those prawns. The decider was the cooking of those prawns.


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[Assistant] Ben, your heads were crispy and your prawns were poached well.


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[Assistant] Although your prawns were inconsistently cooked. That's why, Ben, head over there, you're safe.


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[Assistant] This time of the year mussels are saltier than normal. I have to congratulate you, the fish is cooked well. Thank you. Good job.


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[Assistant] For me, the technique gone into making that folded tortellini is gorgeous. Well done.


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[Assistant] Love that ice cream, it's made beautifully. Delicious. Metta, you're next. I've cooked the traditional


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[Assistant] Spectacular on a plate, spectacular. And you worked, uh, like a demon in the kitchen today. Determined?


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[Assistant] But it's, there's nothing roasted there. It's really clever. It's modern and sophisticated, but super delicious and that's what great cooking's all about.


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[Assistant] To the rest of you, it's now time for you to get out there and make those dreams come true. Keep cooking, keep trying, keep practising, keep working hard and you'll succeed. For the last time, it's time to leave the MasterChef kitchen.


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[Assistant] Aldo is worried about overcooking his prawns. But by doing a tester, I'm worried that he might have used up too much of the fresh herbs in the butter.


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[Assistant] For a French dish, shovels are a very important herb.


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[Assistant] That need to be a prominent flavor in his dish.


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[Assistant] In this video, we'll figure out a slightly simpler way to write the cost function than we have been using so far, and we'll also figure out how to apply gradient descent to fit the parameters of logistic regression.


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[Assistant] So by the end of this video, you know how to implement a fully working version of logistic regression.


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[Assistant] Here's our cost function for logistic regression. Our overall cost function is 1 over m times sum over the trading set of the cost of making different predictions on the different examples of labels y i.


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[Assistant] And this is the cost for a single example that we worked out earlier.


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[Assistant] Y is always equal to 0 or 1, right? That's sort of part of the mathematical definition of Y. Because Y is either 0 or 1,


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[Assistant] We'll be able to come up with a simpler way to write this cost function. And in particular, rather than writing out this cost function on two separate lines with two separate cases for y equals one and y equals zero, I'm going to show you a way to take these two lines and compress them into one equation.


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[Assistant] Expression of this equation is a equivalent way or more compact way of writing out this definition of the cost function that we have up here. Let's see why that's the case.


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[Assistant] We know that there are only two possible cases, y must be 0 or y or 1. So let's suppose y equals 1. If y is equal to 1, then this equation is saying that the cost


[User] Please transcribe this text

[Assistant] Well if y is equal to 1, then this thing here is equal to 1.


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[Assistant] And 1 minus y is going to be equal to 0, right? So if y is equal to 1, then 1 minus y is 1 minus 1, which is therefore 0.


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[Assistant] So the second term gets multiplied by zero and goes away, and we're left with only this first term, which is y times log, minus y times log h of x. y is one, so that's equal to minus log h.


[User] Please transcribe this text

[Assistant] Our writing of the cost function is saying that if y is equal to zero, then this term here would be equal to zero.


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[Assistant] Whereas 1 minus y, if y is equal to 0, will be equal to 1. Because 1 minus y becomes 1 minus 0, which is just equal to 1.


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[Assistant] And so the cost function simplifies to just this last term here.


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[Assistant] Right? Because uhm, the first term over here gets multiplied by zero and so disappears, so we're just left with this last term, which is minus log 1 minus h of x.


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[Assistant] And you can verify that this term here is just exactly what we had for when y is equal to zero.


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[Assistant] So this shows that this definition for the cost is just a more compact way of taking both of these expressions, the cases y equals one and y equals zero, and writing them in one, in a more convenient form with just one line.


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[Assistant] We can therefore write out our cost function for logistic regression as follows.


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[Assistant] It is this 1 over m of the sum of these cost functions, and plugging in the definition for the cost that we worked out earlier, we end up with this, and it just brought the minus sign outside.


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[Assistant] Although I won't have time to go into great detail of this in this course, this cost function can be derived from statistics using the principle of maximum likelihood estimation, which is an idea in statistics for how to efficiently find parameters data for different models.


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[Assistant] You know, essentially everyone uses when fitting logistic regression models.


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[Assistant] If you don't understand the terms that I just said, so that if you don't know what the principle of maximum likelihood estimation is, don't worry about it, but it just, that's just a deep rationale and justification behind this particular cost function, then I'll have time to go into in this class. Given this cost function,


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[Assistant] In order to fit the parameters, what we're going to do then is try to find the parameters theta that minimize j of theta. So if we


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[Assistant] You know, try to minimize this, this would give us some set of parameters theta. Finally,


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[Assistant] If we're given a new example with some set of features x, we can then take the thetas that we fit to our trading set and, uh, output our prediction as this. And just to remind you, the output of my hypothesis I'm going to interpret as the probability that y is equal to 1.


[User] Please transcribe this text

[Assistant] And, uh, this is given the input x and parameterized by theta. I just didn't think of this as just my hypothesis as estimating the probability that y is equal to 1.


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[Assistant] So all that remains to be done is figure out how to actually minimize j of theta as a function of theta so that we can actually fit the parameters to our training set.


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[Assistant] The way we're going to minimize the cost function is using gradient descent. Here's our cost function.


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[Assistant] And uhm, if we want to minimize it as a function of theta, here's our usual template for gradient descent where we repeatedly update each parameter by taking, updating it as itself minus the learning rate alpha times this derivative term.


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[Assistant] If you know some calculus, feel free to take this term and try to compute the derivative yourself and see if you can simplify it to the same answer that I get. But even if you don't know calculus, don't worry about it.


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[Assistant] If you actually compute this, what you get is this equation.


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[Assistant] And I just write it out here. It's sum from i equals 1 through m of the, essentially the error times x i j.


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[Assistant] So if you take this partial derivative term and plug it back in here, we can then write out our gradient descent algorithm as follows.


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[Assistant] And all I've done is I took the derivative term from the previous slide and plugged it in there.


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[Assistant] So if you have n features, you would have, you know, a parameter vector theta, which with parameters theta 0, theta 1, theta 2, down to theta n.


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[Assistant] And you would use this update to simultaneously update all of your values of theta. Now, if you take this update rule and compare it to what we were doing for linear regression, you might be surprised to realize that, well, this equation


[User] Please transcribe this text

[Assistant] Was exactly what we had for linear regression. In fact, if you look in the earlier videos and look at the update rule,


[User] Please transcribe this text

[Assistant] The gradient descent rule for linear regression, it looked exactly like what I drew here inside the blue box.


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[Assistant] So are linear regression and logistic regression different algorithms or not?


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[Assistant] Well, this is resolved by observing that for logistic regression, what has changed is that the definition


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[Assistant] For this hypothesis has changed. So whereas for linear regression we had h of x equals theta transpose x. Now the definition of h of x has changed and is instead now 1 over 1 plus e to the negative theta transpose x.


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[Assistant] So even though the update rule looks cosmetically identical, because the definition of the hypothesis has changed, this is actually not the same thing as gradient descent for linear regression.


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[Assistant] In an earlier video when we were talking about gradient descent for linear regression, we had talked about how to monitor a gradient descent to make sure that it is converging.


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[Assistant] I usually apply that same method to logistic regression too, to monitor gradient descent, to make sure it's converging correctly, and hopefully you can figure out how to apply that technique to logistic regression yourself.


[User] Please transcribe this text

[Assistant] When implementing logistic regression with gradient descent, we have all of these different parameter values, you know, theta zero down to theta n that we need to update using this expression. And one thing we could do is have a for loop, so for i equals zero to n,


[User] Please transcribe this text

[Assistant] Or for i equals 1 to n plus 1 to update each of these parameter values in turn. But of course, rather than using a for loop, ideally we would also use a vectorized implementation. And so that a vectorized implementation can update, you know, all of these n plus 1 parameters all in one fell swoop.


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[Assistant] And to check your own understanding, you might see if you can figure out how to do the vectorized implementation of this algorithm as well.


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[Assistant] So now you know how to implement gradient descent for logistic regression.


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[Assistant] There was one last idea that we had talked about earlier for linear regression, which was feature scaling.


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[Assistant] Feature scaling can help gradient descents converge faster for linear regression.


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[Assistant] The idea of feature scaling also applies to gradient descent for logistic regression.


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[Assistant] And if you have features that are on very different scales, then applying feature scaling can also make Great Innocent run faster for logistic regression.


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[Assistant] So, that's it. You now know how to implement logistic regression and this is a


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[Assistant] Experience here, Samira, Kristen, fourth time here, Khan. Well, you've already won a pin. Brendan, you know what it's like to want a pin.


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[Assistant] You can taste is the instinct that you are gonna nearly cook that for yourself. And that's why it tastes so good.


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[Assistant] What you see here is what you get. There is no underbench pantry today.


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[Assistant] Here's where it's different. Two pantries today. Yep. This one, and a surprise pantry.


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[Assistant] Your choice today is whether to keep your 15 minute head start


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[Assistant] Time to reveal the surprise pantry. Can I do this without Matt Preston?


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[Assistant] Hey Ashley. Shannon. You're seeing me a little quicker today than what you normally would. Follow me. Yeah, right.


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[Assistant] Khan has decided to give up his 15 minute head start. Which means you both now have 60 minutes.


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[Assistant] However you can only use this pantry. This is gonna be an interesting showdown.


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[Assistant] Both of you ready? Yes. Okay, your time starts now.


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[Assistant] Okay, I'm gonna use these vegetables. Kohlrabi, sweet, squash, anything you're worried about?


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[Assistant] I'm still at a bit of a loss at how you're bringing this dish together. At the moment you've just got a duck breast and a sauce. Sure.


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[Assistant] A lot of ginger there, but too much. Ginger's a problem for me.


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[Assistant] Alright. Sure you're not going too sooner? I think so. Okay.


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[Assistant] Looks nice. Two great looking dishes. Well done to both of you.


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[Assistant] Now really it all comes down to the judges. Yep. And what do they prefer?


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[Assistant] Shannon, what went on in the kitchen today? It was a really interesting day. First time I was ever involved where a contestant has given up their extra 15 minutes. Khan gave that up and in return he was given the opportunity to use two pantries.


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[Assistant] Beautiful. So almost a level playing field. Level playing field and I think that both of them did an extremely very, very good job.


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[Assistant] What do you think has been important about the innovation of people's ability to insure against risk in the marketplace, whether it's through just something as simple as uhm, you know, an insurance contract or by other means?


[User] Please transcribe this text

[Assistant] Do you think it's safe to say that historically financial innovation has occurred on the, you know, kind of the upside looking to capture new markets and new


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[Assistant] Ways of of earning returns versus on the kind of the downside risk management, uh, side of the side of the ledger.


[User] Please transcribe this text

[Assistant] The second point is that we want to require supplier quality assurance and implement a zero defects quality program. We currently have far too many errors that lead to defective items, and therefore, they must be eliminated.


[User] Please transcribe this text

[Assistant] A quality control at the source program must be implemented to give workers personal responsibility for the quality of the work they do and the authority to stop production when something goes wrong.


[User] Please transcribe this text

[Assistant] The second point is that we want to require supplier quality assurance and implement a zero defects quality program. We currently have far too many errors that lead to defective items, and therefore, they must be eliminated.


[User] Please transcribe this text

[Assistant] A quality control at the source program must be implemented to give workers personal responsibility for the quality of the work they do and the authority to stop production when something goes wrong.


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[Assistant] It would be my pleasure. Please have a seat. Can I offer you a glass of wine?


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[Assistant] I hope you didn't poison her drink too much. You'll ruin our meal.


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[Assistant] Please, make yourselves at home. Let me take your coats. Dinner is almost ready. I hope you brought your appetite.


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[Assistant] It would be my pleasure. Please have a seat. Can I offer you a glass of wine?


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[Assistant] A very special Merlot brought directly from my home country.


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[Assistant] It has a unique ingredient, which gives it a pleasant aroma and superior flavor.


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[Assistant] I hope that you didn't poison her drink too much. You'll ruin our meal.


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[Assistant] Let's see who's gonna go first. So everyone put your hand on a knife. One, two, three. Ben, you'll be first.


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[Assistant] It's all flavour now, isn't it? Yeah. Yeah, really? It's all flavour.


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[Assistant] That is exactly right. Classic combo of chocolate, vanilla and strawberry.


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[Assistant] You have to hero either chocolate, vanilla, or strawberry. And because it's sweet week, we want a dessert. You got an open pantry, garden is at play.


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[Assistant] Uh, Shannon, the floor's all yours, but I know Gary will want this.


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[Assistant] The flavours were great, but today your cremeux didn't set.


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[Assistant] Justin, I scored your dish a 6 out of 10.


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[Assistant] Kristen, tough one today. I mean, that was so, so close. If we could taste chocolate, it would have been totally different.


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[Assistant] Alice, we know it wasn't the best day for you in the kitchen. No, it wasn't. I mean, these boys don't stop talking about how good your desserts are in your own place. It's tough.


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[Assistant] Picture it. You're right in the middle of binging the latest season of The Great British Bake Off when you suddenly look at the clock and realize it's one in the morning.


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[Assistant] Like, your laptop screen can mess with your body's internal clock. But did using a screen at night really keep you up longer, or was that just Paul Hollywood's beautiful blue eyes? And if you did bring your phone or laptop to bed with you, so that you could just watch one more episode as you drift off, well, that'd actually prevent you from getting a good night's sleep.


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[Assistant] Turns out the answer to both of those questions is probably yes, and getting around the problem might not be as easy as it seems. Your body's internal clock, or circadian rhythm, is regulated by a type of neuron in your eyes


[User] Please transcribe this text

[Assistant] Specifically, they are most sensitive to a wavelength of 482 nanometers, which is a sort of turquoisey blue that is a big component of daylight. The thing is,


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[Assistant] Screens emit some blue light too, which tricks the ganglion cells into thinking there's still some daylight out there, so it might not be time to sleep just yet. Studies have suggested that when people are exposed to blue light before they go to sleep, they get less total sleep and wake up more frequently over the course of the night. This isn't necessarily something you can fix with a cup of coffee in the morning, either. Studies have found that long-term disruption of your body's circadian rhythm is associated with a wide range


[User] Please transcribe this text

[Assistant] It's important to note that so far, most of the studies on blue light have been observational, meaning that they looked at what happened but didn't control the amount of light to see if it actually caused the sleep problems. Many have also been small or used animal subjects instead of humans. So we don't have conclusive evidence that your daily late-night scrolling actually causes sleep or health problems.


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[Assistant] But we've seen that they tend to go together. Let's be real here, though. Most of us aren't gonna stop using our phones or computers after dark. That's some of the best time.


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[Assistant] For phones and computers. So there are other options, like software that makes your screen emit less blue light when it's dark out, or special glasses with tinted lenses that filter out blue light. Unfortunately, researchers haven't been able to consistently demonstrate that those programs or glasses actually do anything. It doesn't necessarily mean that blocking blue light is ineffective, it's just that so far the studies on these approaches have had too many flaws to draw any conclusions. Maybe you're sensing a theme.


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[Assistant] We need better studies into the problems with blue light and how to address them. But for now, we know enough to say that it's probably worth stopping the TV binge just a little early. No matter how desperately you want to find out if Stacey gets eliminated, your body will thank you. And no spoilers in the comments about who's the greatest British baker.


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[Assistant] Come on, Sarah. Everyone's neck and neck, like. Everyone's pretty much at the same spot. In fact, same spot.


[User] Please transcribe this text

[Assistant] Chocolate, macadamia and seasonal fruits.


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[Assistant] It's always tough being in elimination. At this stage we're all producing amazing food, so you really need to step up your game.


[User] Please transcribe this text

[Assistant] I've been working so hard trying to learn more, practice every day.


[User] Please transcribe this text

[Assistant] My parents came over to Australia from Vietnam on a leaky boat.


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[Assistant] I felt like I didn't really fit in. I was a bit of an outsider.


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[Assistant] Whenever I came home after school, I would hang out in the kitchen with mum. And so that's where my love for food really started to grow.


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[Assistant] Not at all. None of us want to be 11th. We want to make that top 10 and we're so close and it's just a step closer we make it to the end. And we all want to be there. We all want to win.


[User] Please transcribe this text

[Assistant] As soon as I saw a cinnamon, I thought of a cinnamon whiskey. Yeah, nice. I'm gonna do that into a caramel, I think. Do it with an ice cream. And like, you know how sticky date has cinnamon in it? I'm just gonna boost that.


[User] Please transcribe this text

[Assistant] Today, the dish that I'm cooking is called my Drunken Sticky Date.


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[Assistant] I'm really happy with the whole concept behind this dessert, but my biggest concern is not getting the ice cream to set in time.


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[Assistant] Today's elimination is massive. We're cooking for Kirsten Tibbles and we need to make a dessert either harrowing coconut, cinnamon, banana or almonds.


[User] Please transcribe this text

[Assistant] You need to get it in, Khan. I know. Hopefully it sets in time.


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[Assistant] I have my sticky day pudding in the oven. My ice cream is churning. I need to get started on my whiskey caramel now.


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[Assistant] I feel really happy. Like, I know that it's in the judges' hands right now, but I'm proud of the dish that I put up. I really would hope that I'm in top 10. I have a good feeling about this, so I'm just keeping my fingers crossed.


[User] Please transcribe this text

[Assistant] It's my drunken sticky date. It's a sticky date pudding with a cinnamon ice cream, a salted crumb and a cinnamon whiskey caramel.


[User] Please transcribe this text

[Assistant] I think so. I hope so. I'm really happy with everything that I've presented to you guys here. I'm really proud of what I'm putting up today.


[User] Please transcribe this text

[Assistant] Looks fabulous, doesn't it? Thank you. Cheers. Enjoy, guys.


[User] Please transcribe this text

[Assistant] When you walk in here on pressure test day, there's only two things on your mind.


[User] Please transcribe this text

[Assistant] You're hoping for the best, but you fear the worst. Good luck to each and every one of you. But you know the score. At the end of today, somebody is going home.


[User] Please transcribe this text

[Assistant] Oh, absolutely. Delicious food. All sorts of things. From, you know, from the tandoor, from, from the charcoal, from the pot.


[User] Please transcribe this text

[Assistant] You have two and a half hours to recreate Syrangia's butter chicken and the three accomplishments. The Romali roti, the pickled onions, and of course the chutney.


[User] Please transcribe this text

[Assistant] Everything that you need, all your ingredients and the recipes are at your benches.


[User] Please transcribe this text

[Assistant] Yeah, keep it up. Listen up guys, 90 minutes to go. Come on!


[User] Please transcribe this text

[Assistant] Yeah, this smells good because you've got a bit of smoke going on. So this is replicating the tandoor, right? So you need a bit of the char and a bit of that smoky flavour.


[User] Please transcribe this text

[Assistant] Her chicken is not on. Yeah, I know. And, you know, time's the ticket. Still a lot to do, yeah?


[User] Please transcribe this text

[Assistant] Talked about hope or fear at the beginning of the day. You couldn't have hoped for anything better.


[User] Please transcribe this text

[Assistant] You know what's noticeable about this butter chicken? It's just the colour of the sauce. Really stands out. It's almost identical to yours.


[User] Please transcribe this text

[Assistant] I'm searching for faults. Yeah. I'm trying to go, okay, is the, you know, is the onion good enough? The Romali, is it thin enough? Is it toasty enough? I think it's, it's pretty damn close to yours, Saranch. It really is. I can't believe it.


[User] Please transcribe this text

[Assistant] You get a sense sometimes when you walk in the kitchen, this is what we hear from past contestants, that they know when they're going home.


[User] Please transcribe this text

[Assistant] You know what? It's got some punch, it's got texture, it's pushed and I quite like that. And certainly not subtle in any way. So it's tasty, but then once you reference your dish, Sriranch, then you realise that it's kind of way off. She's careered off into a different zone.


[User] Please transcribe this text

[Assistant] Not quite ready to go home yet, no?


[User] Please transcribe this text

[Assistant] I think Sarah's chutney was good, and I kinda like the smoky char of Sarah's chicken. And I think Jess is underwhelming in terms of that, you know, clear identity of the, of the grill or the tandoor. Tug of war between those two dishes.


[User] Please transcribe this text

[Assistant] We talked about your hopes and fears at the beginning of the day, and when Saranj popped that cloche on his Goyla Butter Chicken.


[User] Please transcribe this text

[Assistant] We don't think we could have hoped for a better pressure test dish.


[User] Please transcribe this text

[Assistant] And it proved to be a classic, full of twists and turns, and the perfect challenge.


[User] Please transcribe this text

[Assistant] To prove that you deserve your place in this competition.


[User] Please transcribe this text

[Assistant] Well, that is high praise indeed, Mr. Goyler. And Chloe, congratulations. You are safe.


[User] Please transcribe this text

[Assistant] First I get onto a cinnamon sponge for my cake pops.


[User] Please transcribe this text

[Assistant] I am always wanting to be a role model for my own kids and to teach them that no matter what goals you set for yourself, you can go for it.


[User] Please transcribe this text

[Assistant] Good girl. Top 10s up for grabs. I've got my game face on today.


[User] Please transcribe this text

[Assistant] It's not a typical sponge texture that I'm after. I want that dense, fudge texture.


[User] Please transcribe this text

[Assistant] I've got a hero cinnamon and all I'm thinking about is cinnamon. Cinnamon in everything. Cinnamon in my pegs, cinnamon in the chocolate, cinnamon in the meringue.


[User] Please transcribe this text

[Assistant] I have no idea how to balance that cinnamon.


[User] Please transcribe this text

[Assistant] I'm using cinnamon in every element. There's just too much cinnamon. I have to work out how to balance that cinnamon so that it's not too overpowering.


[User] Please transcribe this text

[Assistant] So I decided to make a orange zest sugar to sprinkle onto the cake pop.


[User] Please transcribe this text

[Assistant] I take my cake pops, dip it in the chocolate and then sprinkle some of my orange zest sugar, pipe a bit of the meringue on top and lightly torch it.


[User] Please transcribe this text

[Assistant] They are a fun little treat that my kids absolutely love to eat and I hope the judges enjoy it.


[User] Please transcribe this text

[Assistant] It is about fun and the cinnamon flavour is definitely there as well as the orange zest.


[User] Please transcribe this text

[Assistant] I hope I've done enough to balance that cinnamon flavour.


[User] Please transcribe this text

[Assistant] I've made cinnamon meringue cake pops.


[User] Please transcribe this text

[Assistant] It's not a plated dessert, but it's something fun. This is me, it's what I love doing.


[User] Please transcribe this text

[Assistant] Look, I certainly hope so. I'm up against some great cooks and some fantastic competition and at this stage, you know, we really need to lift our game. So I'm really going to say I hope so.


[User] Please transcribe this text

[Assistant] I mean look, Backlovers on the top of the list. And you bring us cake pops. And I brought you cake pops.


[User] Please transcribe this text

[Assistant] The opportunity to, and the journey's been just so amazing to...


[User] Please transcribe this text

[Assistant] Get mentoring from you guys, just a dream come true. From how far I've come, from where I was just a few months ago to now, I've grown and, and, you know, it just has ignited that passion even more to keep going and, you know, I never give up, so.


[User] Please transcribe this text

[Assistant] Feeling pretty gutted. It's such a shame to go at this point, but I'm so thankful and grateful for the opportunities that I've had.


[User] Please transcribe this text

[Assistant] I was just a homecook, a mum cooking for her family, jazzing a few meals up here and there.


[User] Please transcribe this text

[Assistant] To this competition where I've cooked for Nigella, for Gordon, for the most amazing chefs across the country.


[User] Please transcribe this text

[Assistant] This is something that I never dreamed I'd be doing.


[User] Please transcribe this text

[Assistant] I'm happy and proud that I've been able to come here and showcase my absolute passion in food. I just can't wait to take this further. I'm just going to be guns blazing, going to follow my food dream. The sky's the limit now.


[User] Please transcribe this text

[Assistant] It's now finally time for your very first coding challenge.


[User] Please transcribe this text

[Assistant] So coding challenges are basically coding exercises that you have to code on your own. And they are super important for you to test and reinforce all the skills that you just learned before.


[User] Please transcribe this text

[Assistant] That's why there are dozens of coding challenges in this course, because students love them and they are one of the best ways of learning.


[User] Please transcribe this text

[Assistant] And so this is the coding challenge number one of the section. Or coding exercise, if you prefer to call it that.


[User] Please transcribe this text

[Assistant] Now all of these coding challenges are also in a separate PDF file that is available somewhere in the course. So you can also get this text from there. You don't have to read the video. Okay.


[User] Please transcribe this text

[Assistant] Now anyway, the exercise is this. Mark and John are trying to compare their body mass indexes. And the BMI is calculated using this formula.


[User] Please transcribe this text

[Assistant] So BMI is equal to mass divided by the height squared. Okay, and so squared is the exponentiation operator that we talked about before with the 2.


[User] Please transcribe this text

[Assistant] Okay. And so that is also the same to mass equals height times height. Okay. So this part is the same as this one. So you can choose to calculate the BMI either way.


[User] Please transcribe this text

[Assistant] Now what matters is that the mass needs to be in kilograms and the height needs to be in meters. So it's not going to work with the US measures like feet and pound. But that's why I have the test data here already with the correct measurements.


[User] Please transcribe this text

[Assistant] Anyway, here is what I want you to do for this challenge. One, you should store Mark's and John's mass and height in variables. And you should do this for test data one.


[User] Please transcribe this text

[Assistant] So this data here, and then also for test data too.


[User] Please transcribe this text

[Assistant] Alright, then using these variables, calculate both their BMIs using the formula that I just showed you. And again, you can use either one. It's going to work the same way. Of course, to then check these values, if they make sense, you can log them to the console, just like we have been doing up until this point.


[User] Please transcribe this text

[Assistant] Finally, I want you to create a boolean variable called markHigherBMI, which will contain the information whether Mark has a higher BMI than John. Okay? And this is actually similar to something that we did before, so I hope that you can make this one work just fine.


[User] Please transcribe this text

[Assistant] So now, please really try to solve this problem on your own.


[User] Please transcribe this text

[Assistant] And remember the advice that I gave you in the beginning. Don't try to make this perfect for now. What matters is really just to make it work. Doesn't matter if you write clean code or perfect code or efficient code. Just make it work for now. All right?


[User] Please transcribe this text

[Assistant] So pause the video now and I see you in a second with the solution.


[User] Please transcribe this text

[Assistant] Alright, I hope you managed to complete all the three points of this challenge. And so here is how I would have implemented it.


[User] Please transcribe this text

[Assistant] So I'm starting with number one of course, and so let's say const mass mark equals 78. Okay, so that's just what is written here. And then, uh, height.


[User] Please transcribe this text

[Assistant] And then the same for John. So math, John equals 92.


[User] Please transcribe this text

[Assistant] And if you used different variable names, that's not a problem at all. As long as they are nicely descriptive, like these ones here, you're going to be fine. Also, you might have used, uh, let here instead of const, because you might assume that these are values that are susceptible to change, especially here, the mass, right?


[User] Please transcribe this text

[Assistant] However, I still decided to use const because I already know that I'm not going to change these values here throughout the program.


[User] Please transcribe this text

[Assistant] And so just as we learned before, I prefer to always use const by default. And I advise you to actually do the same.


[User] Please transcribe this text

[Assistant] Okay. Anyway, let's now calculate the actual BMI's. So const BMI mark equals


[User] Please transcribe this text

[Assistant] Mass mark divided, let's check out the formula again, divided by the height squared. So, that's gonna be, uh, height mark squared.


[User] Please transcribe this text

[Assistant] And then the BMI, uh, John.


[User] Please transcribe this text

[Assistant] So that's Math John, and this time let's actually use the other formula. So this one here. So we're going to use, uh,


[User] Please transcribe this text

[Assistant] Hide John times Hide John again. Okay. And now let's lock both of them to the console here. So BMI Mark and BMI John.


[User] Please transcribe this text

[Assistant] And now we have an error here. Oh, of course, I missed the dot lock.


[User] Please transcribe this text

[Assistant] Okay, try it again, and here we go.


[User] Please transcribe this text

[Assistant] So we see that BMI mark is higher than John's BMI.


[User] Please transcribe this text

[Assistant] Okay, so I hope you got the same numbers here. Then I did. And if not, I guess you should probably check your code. Unless I have some mistake here. Let me check that actually. Uh, but I think everything is good.


[User] Please transcribe this text

[Assistant] Okay, so if something is wrong, then please just let me know. Alright?


[User] Please transcribe this text

[Assistant] Now, if you implemented this in a different way, for example, you might not have created these separate variables here, then that's not a problem at all.


[User] Please transcribe this text

[Assistant] Okay, you could have logged these calculations straight to the console. No problem at all. Again, what matters here is that you make this work and that in the end you get these same results here.


[User] Please transcribe this text

[Assistant] Anyway, let's now also, uh, do step three and create a variable called markHigherBMI. So let's just grab this here.


[User] Please transcribe this text

[Assistant] And so what we're trying to figure out is if the BMI of Mark is higher than the BMI of John.


[User] Please transcribe this text

[Assistant] Right? And so that's what comparison operators are for. Because remember that this one here will return either true or false.


[User] Please transcribe this text

[Assistant] In our example, if BMI mark is larger than the one of John, then the result of this whole operator here will be true. And otherwise, it's gonna be false.


[User] Please transcribe this text

[Assistant] Okay, so that's exactly what we did before in this example with the, with the ages, if I remember correctly. So where's that? Ah, yeah, it's right here. In this case, it was the isFullAge variable, right?


[User] Please transcribe this text

[Assistant] Okay. Anyway, let's log it here to the console as well.


[User] Please transcribe this text

[Assistant] And so we expect this one to be, uh, true, right? Because Mark's BMI is 27 and John's is 24. And so Mark's is larger, and so the result of this should be true. So let's check that.


[User] Please transcribe this text

[Assistant] And indeed we get true. Nice. So we basically solved it. Now I just want to do the same here for test data too. So we'll just copy this. So copy. And then I will simply comment out these first ones.


[User] Please transcribe this text

[Assistant] So now I'm replacing these with 95, 188.


[User] Please transcribe this text

[Assistant] And then here for John we have 85 and 176.


[User] Please transcribe this text

[Assistant] And the rest, of course, is the same. And that's the beauty of using variables. Because now all we have to do is to change these values in one place, and then the changes will be propagated to the rest of the code here, which references these variables.


[User] Please transcribe this text

[Assistant] Now BMI of John is 27, so it's larger than 26.8.


[User] Please transcribe this text

[Assistant] It's actually very close, but still, uh, BMI Mark is now lower than BMI John. So here we ask the question, basically, is BMI Mark larger than BMI John?


[User] Please transcribe this text

[Assistant] And in this case, it's not, so it's false. And so that's exactly the result that we get here.


[User] Please transcribe this text

[Assistant] Alright, so this one is solved and I hope you solved it as well. Again, it does not matter at all if you did it in a different way, as long as the results were the same. So basically as long as you actually made it work.


[User] Please transcribe this text

[Assistant] Hopefully that was a lot of fun and you could practice your skills a little bit, which is really something essential to learn programming, uh, properly. Without repetition and reinforcing your knowledge, it's impossible really to learn how to code.


[User] Please transcribe this text

[Assistant] Anyway, see you now in the next video where we're going to continue learning the fundamentals of the beautiful JavaScript language.


[User] Please transcribe this text

[Assistant] I've done this dark curry before and it tastes amazing. So, I would like the judges to also taste it and, uh, feel the same thing.


[User] Please transcribe this text

[Assistant] I've spent an hour and a half prepping the duck. I need to start the curry sauce now.


[User] Please transcribe this text

[Assistant] Once the curry paste starts to boil, I add chopped lychee.


[User] Please transcribe this text

[Assistant] I need to make sure the sweetness from the lychee is in a good balance in the curry sauce.


[User] Please transcribe this text

[Assistant] I need to shear the duck, render the fats, get a golden crispy skin, then put it in the oven for 8 minutes. It's gonna be very close.


[User] Please transcribe this text

[Assistant] Just minutes before service, all my elements are ready. My duck is out of the oven. My curry sauce is ready. I'm ready for service.


[User] Please transcribe this text

[Assistant] Starting in the 19th century, information technology began to develop. There was a man named Reuter who in, just before the invention of the telegraph,


[User] Please transcribe this text

[Assistant] Decided that stock markets need up-to-date information and so he thought how can I get information fair? I'll sell information. So what he did is these pigeons fly faster than any human


[User] Please transcribe this text

[Assistant] Transport. You know, carrier pigeons. So what he did is he set up offices in major European cities and bought pigeons


[User] Please transcribe this text

[Assistant] And as soon as some market event happened in London, he would tie a piece of paper, uh, to the leg of the pigeon, uh, in Paris, in London, and send the news to Paris.


[User] Please transcribe this text

[Assistant] And how long would it take a pigeon to fly from London to Paris? I don't know.


[User] Please transcribe this text

[Assistant] So it gave a trading advantage to people. So he, he was a big success with his pigeon service. Uh, and later when they invented the telegraph, uh, that was here in New Haven by the way, Samuel F.B. Morris invented the telegraph. What year was that?


[User] Please transcribe this text

[Assistant] The, uh, uh, writers went to the telegraph to speed it up even more. By the late 19th century, everyone was getting information with the speed of electricity.


[User] Please transcribe this text

[Assistant] Uh, and they got beepers in the 20th century installed that would beep them when there was some important news. Uh, they would carry that around. Even before you had a cell phone, you could get a beeper.


[User] Please transcribe this text

[Assistant] Uh, so the idea is that the information, there's so many smart people trying to get information that, uh, it must be hard to beat the market. And that means that you really can't predict it. So the random walk became


[User] Please transcribe this text

[Assistant] Plausible because people thought, yeaah, all these people are trying so hard to get the information as quickly as they can and they trade on it as soon as they get it.


[User] Please transcribe this text

[Assistant] So if the London market falls, you would like to sell in Paris. The problem is you can't get the information in Paris fast enough. But now that they get it really fast, the market must adopt, uh, almost, uh, adjust almost immediately.


[User] Please transcribe this text

[Assistant] So, so this is what it came to. The reason efficient market sounds plausible is you have to educate people out of naive


[User] Please transcribe this text

[Assistant] Then the broker will tell you, you read it when? Last week?


[User] Please transcribe this text

[Assistant] He said, well, when that, your broker might say, when that news came out, I remember my beeper went off immediately and I rushed to my colleagues and said, what's this news mean? And someone said, sell, sell right now.


[User] Please transcribe this text

[Assistant] And so I placed an order in 15 seconds. He had said, you gotta beat the others.


[User] Please transcribe this text

[Assistant] Uh, and then, then I said I just sold but I hadn't even had 15 seconds to talk about it. They talk more about it and they think, well maybe I shouldn't have sold. So 30 seconds later, you buy.


[User] Please transcribe this text

[Assistant] And then within two minutes, they've gotten expert advice on what it means.


[User] Please transcribe this text

[Assistant] And the market has gone wild and now it settles down at the new optimal level. So maybe the market wasn't perfectly efficient for 15 seconds. But you had better be educated that if you read something in the newspaper last week, it's already incorporated into market prices.


[User] Please transcribe this text

[Assistant] Here's a 1904 article, it's a really nice article, uh, by, uh, Charles Conant, uh, in, uh, in a magazine, uh, and it's about the beauty of markets.


[User] Please transcribe this text

[Assistant] Uh, and he was referring to the, uh, public, he referred to an ignorant public view that markets are a sort of gambling casino. But he said a moment's reflection should convince such a person that a function which occupies so important a place in the mechanism


[User] Please transcribe this text

[Assistant] What he's getting at is that, uh, those prices in markets are the result of people trying to figure out values.


[User] Please transcribe this text

[Assistant] And if we didn't have the markets, we wouldn't know what anything was worth.


[User] Please transcribe this text

[Assistant] Any business plan involves prices. As a business you're going to have to buy commodities or you're going to have to borrow at interest rate. All these prices are relevant to an intelligent decision.


[User] Please transcribe this text

[Assistant] So, not only are markets efficient, according to Conant,


[User] Please transcribe this text

[Assistant] And then it produces values which he implicitly assumes in 1904 are the best estimate of fundamental value. And then it drives businesses. Businesses then make decisions for whether to build a new factory or to hire new people.


[User] Please transcribe this text

[Assistant] Based on these prices. So it's a beautiful system that he talks about.


[User] Please transcribe this text

[Assistant] In defense of the financial market, uh, even your textbook, uh, Fabozzi in an earlier edition in 2002, uh, said publicly available relevant information will lead to correct pricing of freely traded securities in properly functioning markets.


[User] Please transcribe this text

[Assistant] Uh, here's another textbook of finance, uh, by Richard Breely and Stuart Myers.


[User] Please transcribe this text

[Assistant] And in an earlier edition, efficient markets really took hold the theory in people's thinking starting after Burton Malkiel's book. It really was a intellectual revolution. But according to Brie Lee Myers and Alan,


[User] Please transcribe this text

[Assistant] Security prices accurately reflect available information and respond rapidly to new information as soon as it becomes available. That's a pretty strong statement.


[User] Please transcribe this text

[Assistant] Uh, but, and then they did qualify. Don't misunderstand the efficient markets idea. It doesn't say that there are no taxes or costs. It doesn't say that there aren't some clever people and some stupid ones.


[User] Please transcribe this text

[Assistant] It merely implies that competition in capital markets is very tough.


[User] Please transcribe this text

[Assistant] He's not really qualifying, they're not really qualifying it very much. They're telling you to believe prices you see in the markets as if they were truth.


[User] Please transcribe this text

[Assistant] They have subsequently, however, in their 2008 edition, this is after the beginning of the financial crisis, they have qualified it. I don't mean to laugh, they're great people. They're reflecting, when you write a textbook, the ideas of the time. But I'm just using this as a sign of how much, uh,


[User] Please transcribe this text

[Assistant] Thinking has changed. They now say much more research is needed before we have a full understanding of why asset prices sometimes get so out of line with what appears to be their discounted future payoffs.


[User] Please transcribe this text

[Assistant] So the efficient markets hypothesis has taken a hit after the financial crisis and you can see it in the textbook.


[User] Please transcribe this text

[Assistant] That's a problem. So I think efficient markets is like that. It was a scientific revolution that came out really in the 60s and then the 70s.


[User] Please transcribe this text

[Assistant] And it led to the extreme bull market that we had around the world in the 1990s. People then finally decided that whatever the stock market does is right. Whatever the housing market does is right because its markets are efficient.


[User] Please transcribe this text

[Assistant] And that unfortunately wasn't quite right. Harry Roberts.


[User] Please transcribe this text

[Assistant] It's, uh, the coiner of the term efficient markets. Although I've traced the history back almost a hundred years before him, they didn't call it efficient markets hypothesis. He said there are three forms for market efficiency. Weak form is that information in past prices can't help you to forecast.


[User] Please transcribe this text

[Assistant] The semi-strong form of efficient markets is that


[User] Please transcribe this text

[Assistant] All publicly information is already incorporated into market prices. And the strong form is that all information, including inside information,


[User] Please transcribe this text

[Assistant] Uh, held by the companies, uh, is already incorporated into stock prices because it leaks out, uh,


[User] Please transcribe this text

[Assistant] Companies can't keep secrets. Actually, I think the semi-strong form is the one that we focus on. I don't think that companies can't keep secrets. They sometimes leak out, but they don't always leak out.


[User] Please transcribe this text

[Assistant] I actually am a big admirer of Eugene Fama, and his papers on this were very interesting.


[User] Please transcribe this text

[Assistant] So, I said that. Eugene Fama would be pleased to hear this.


[User] Please transcribe this text

[Assistant] Listening to efficient markets theory might say that the head of a central bank should never comment on the stock market.


[User] Please transcribe this text

[Assistant] Certain anomalies have appeared. For example, buying stocks with low price earnings ratios has paid off historically for a long time. I think that that's probably best explained by psychological theories.


[User] Please transcribe this text

[Assistant] You've got some natural yoghurt, coriander seed, almonds, some lemon, some dry gin, some Cobram extra virgin olive oil,


[User] Please transcribe this text

[Assistant] You've got some mint, and you've got these. Anyone know what these are? Calettes. Calettes.


[User] Please transcribe this text

[Assistant] They're like the little child of a Brussels sprout and kale. This could be the best of things, or it could be your worst nightmare.


[User] Please transcribe this text

[Assistant] Normally with the mystery box we only ask you to use one ingredient in your dish. But this mystery box is the everything box.


[User] Please transcribe this text

[Assistant] You have to use every one of those ingredients in the one dish.


[User] Please transcribe this text

[Assistant] You have 60 minutes to bring us a dish using every ingredient in the mystery box. Plus, you'll also have your usual underbench pantry.


[User] Please transcribe this text

[Assistant] We'll only be tasting the three most appealing dishes. Bring us the best dish.


[User] Please transcribe this text

[Assistant] And you go straight through to this week's immunity challenge. Are you ready?


[User] Please transcribe this text

[Assistant] We wanted to be delicious, we wanted to be able to identify all the ingredients. I think there are going to be lots of dishes that are highly intriguing.


[User] Please transcribe this text

[Assistant] Just a teaspoon. Uhm, how's your flatbread work now?


[User] Please transcribe this text

[Assistant] Oh that's, that's really tender. You are a master when it comes to bread, aren't you?


[User] Please transcribe this text

[Assistant] So the Jinja challenge, yeah? Find the connection with some things that already exist in the dish and then work out how to partner it. Okay?


[User] Please transcribe this text

[Assistant] What have we got? Six minutes to go. You're not leaving yourself enough time.


[User] Please transcribe this text

[Assistant] We love the fact you're teaching other people how to make it, because you know, even if you give them all your secrets, they haven't got your fingers, and no one makes bread quite as light as you do, so well done.


[User] Please transcribe this text

[Assistant] Cracker is so special. Isn't it? It's kind of bubbly and light and just falls apart just enough when you bite into it. So double win. Gee. Have a competition.


[User] Please transcribe this text

[Assistant] Top ten and I think the best thing for the three of us is that every one of your ten dishes had something to recommend it. So congratulations, the three we tasted, outstanding.


[User] Please transcribe this text

[Assistant] Each of them, wonderful in their own way. Samira, we loved your breakfast dish, we loved the bread. Kristen, brilliant.


[User] Please transcribe this text

[Assistant] That pesto and then with the yoghurt on that beautiful crispbread brilliant and khan tandoori kelettes are undoubtedly a thing. But the winning dish today, the dish I think we just marginally liked a wee bit more


[User] Please transcribe this text

[Assistant] The best three dishes will join Khan in the immunity challenge. On the downside, the contestants to make the three least impressive dishes will face off in tomorrow's pressure test. Nice and clear.


[User] Please transcribe this text

[Assistant] Spectacular cooking, uhm, I'm absolutely with George. This is heaven. Well done.


[User] Please transcribe this text

[Assistant] So what did you do with the apples? Did you peel them, juice them?


[User] Please transcribe this text

[Assistant] Oh, okay. On a day of brilliant dishes, this isn't a brilliant dish.


[User] Please transcribe this text

[Assistant] I like the crispness of the waddle seed wafer, but the sorbet, the apple flavour is good, but it's, it's kind


[User] Please transcribe this text

[Assistant] Yeah, clean the plate, guys. I am. Good. It's a kind of a never ending...


[User] Please transcribe this text

[Assistant] What you've done is you've brought us all the things that people don't like about cheesecake, the way it sticks through your mouth. Uhm.


[User] Please transcribe this text

[Assistant] If I call your name, please step forward. You're in this week's immunity challenge. Brendan!


[User] Please transcribe this text

[Assistant] Congratulations Brendan, Kristen, Samira. The three of you will join Khan this week's immunity challenge.


[User] Please transcribe this text

[Assistant] Let's learn about the switch statement, which is an alternative way of writing a complicated if-else statement when all we want to do is to compare one value to multiple different options, basically.


[User] Please transcribe this text

[Assistant] So in this example, let's say we have a weekday variable and for each day there is a different activity. So basically we're going to map one activity to each day.


[User] Please transcribe this text

[Assistant] Now, maybe you're wondering why I'm basically hard-coding all these variables and how this would work in the real world.


[User] Please transcribe this text

[Assistant] Well, in a real application that's used by users in the browser, usually most of the data comes from user input. And so then we wouldn't be hard coding all of this stuff. Okay. But right now, well, we are just learning how to code. And so it's absolutely no problem at all to just hard code all of these values here. Okay.


[User] Please transcribe this text

[Assistant] Now anyway, going back to our example here, let's now essentially map one activity to each day. So Monday, Tuesday, Wednesday, Thursday, Friday, Saturday and Sunday.


[User] Please transcribe this text

[Assistant] And for that, we could use an if-else statement with multiple else if blocks, but we can also use the easier-to-use switch statement.


[User] Please transcribe this text

[Assistant] So, let me just write how that works, and then I'm going to explain it in a bit more detail.


[User] Please transcribe this text

[Assistant] So what we're switching is basically the day. So this is what we're going to compare to multiple options.


[User] Please transcribe this text

[Assistant] Then we need the curly braces to define a block and then we can define cases. So let's say case Monday.


[User] Please transcribe this text

[Assistant] Then this colon, and notice how it's a colon and not a semicolon like this.


[User] Please transcribe this text

[Assistant] Then another indentation, and then here comes the code that we want to do. So as always, we log something to the console. And once more in a real world app, we will of course not be logging stuff to the console all the time. This is once more just so that we can learn how all this different stuff works.


[User] Please transcribe this text

[Assistant] So let's say on Monday, I plan my course structure.


[User] Please transcribe this text

[Assistant] And here we can, uh, actually execute multiple lines of code. And we don't need curly braces for that. So after the case and the colon, all the lines are then executed.


[User] Please transcribe this text

[Assistant] Okay. And the syntax of this switch statement is actually a little bit unusual. So it's unlike anything else in JavaScript, but well, that's just how it is implemented, I guess.


[User] Please transcribe this text

[Assistant] So anyway, we will execute two console.logs here. So the second one is go to coding meetup.


[User] Please transcribe this text

[Assistant] Okay, so basically what this will do is it will compare day to Monday here in a strict equality way. So this here is basically writing day equal