{"action":"opened","issue":{"url":"https://api.github.com/repos/jmetaxas/date-a-scientist/issues/1","repository_url":"https://api.github.com/repos/jmetaxas/date-a-scientist","labels_url":"https://api.github.com/repos/jmetaxas/date-a-scientist/issues/1/labels{/name}","comments_url":"https://api.github.com/repos/jmetaxas/date-a-scientist/issues/1/comments","events_url":"https://api.github.com/repos/jmetaxas/date-a-scientist/issues/1/events","html_url":"https://github.com/jmetaxas/date-a-scientist/issues/1","id":379481090,"node_id":"MDU6SXNzdWUzNzk0ODEwOTA=","number":1,"title":"Final Grade","user":{"login":"quuu","id":32676955,"node_id":"MDQ6VXNlcjMyNjc2OTU1","avatar_url":"https://avatars0.githubusercontent.com/u/32676955?v=4","gravatar_id":"","url":"https://api.github.com/users/quuu","html_url":"https://github.com/quuu","followers_url":"https://api.github.com/users/quuu/followers","following_url":"https://api.github.com/users/quuu/following{/other_user}","gists_url":"https://api.github.com/users/quuu/gists{/gist_id}","starred_url":"https://api.github.com/users/quuu/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/quuu/subscriptions","organizations_url":"https://api.github.com/users/quuu/orgs","repos_url":"https://api.github.com/users/quuu/repos","events_url":"https://api.github.com/users/quuu/events{/privacy}","received_events_url":"https://api.github.com/users/quuu/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-11-11T02:00:18Z","updated_at":"2018-11-11T02:00:18Z","closed_at":null,"author_association":"NONE","body":"## Valid Python Code:\r\n* Grade: 4/4\r\n* Comments: Code included runs without any errors\r\n\r\n## Exploration of Data:\r\n* Grade: 4/4\r\n* Comments: Data is explored significantly, and the experimental question(s) chosen are logical and based on the data exploration. Features chosen to answer the question make sense. Learner explained the results from LR vs KNN Regression and KNN Classification VS SVM Classification very well and with lots of details. Learner truly understands these statistical methods and their applications.\r\n\r\n## Machine Learning Techniques used correctly:\r\n* Grade: 4/4\r\n* Comments: Algorithms are used correctly and the correct conclusions are drawn from the results.\r\n\r\n## Report: Are conclusions clear and supported by data?\r\n* Grade: 4/4\r\n* Comments: Questions are stated clearly. The results of 2 regression algorithms and 2 classification algorithms are shown. Conclusions are clearly stated and based on evidence. \r\n\r\n## Code Formatting:\r\n* Grade: 4/4\r\n* Comments: Code is formatted clearly and readable. Learner went above and beyond and separated unique functions and classes into respective folders. Followed a very object oriented programming style. Would reward bonus points if possible.\r\n\r\n## Overall\r\n* Grade: 20/20\r\n* Comments: Learner understands machine learning to an experienced level and created excellent models and statistical conclusions from data given and techniques learned. No complaints about the project, every aspect of the project exceeded expectations."}}
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