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* Thursday: Wrapping up PCA from last week, Clustering and basics of decision trees, classification and regression algorithms
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* Friday: Decision trees, voting models and bagging
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!bblock Videos
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o "Video on Decision trees":"https://www.youtube.com/watch?v=RmajweUFKvM&ab_channel=Simplilearn"
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o "Video on Principal Component Analysis":"https://www.youtube.com/watch?v=FgakZw6K1QQ&ab_channel=StatQuestwithJoshStarmer"
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o "Video on Clustering":"https://www.youtube.com/watch?v=esmzYhuFnds&ab_channel=MITOpenCourseWare"
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!eblock
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Geron's chapter 6 covers decision trees while ensemble models, voting and bagging are discussed in chapter 7. See also lecture from "STK-IN4300, lecture 7":"https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf". Chapter 9.2 of Hastie et al contains also a good discussion.
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!bblock Reading
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o Decision Trees: Geron's chapter 6 covers decision trees while ensemble models, voting and bagging are discussed in chapter 7. See also lecture from "STK-IN4300, lecture 7":"https://www.uio.no/studier/emner/matnat/math/STK-IN4300/h20/slides/lecture_7.pdf". Chapter 9.2 of Hastie et al contains also a good discussion.
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o Clustering and PCA, see Geron's chapter 8 and "Lecture notes":"https://compphysics.github.io/MachineLearning/doc/LectureNotes/_build/html/chapter8.html"
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!eblock
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!split
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===== Thursday, Principal Component Analysis =====
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