Stanford CS229: Introduction to Machine Learning : Anand Avati
Youtube Playlist
Playlist - Stanford CS229 2019 Anand Avati
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Introduction and Linear Algebra - https://www.youtube.com/watch?v=KzH1ovd4Ots&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=1
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Matrix Calculus - https://www.youtube.com/watch?v=b0HvwszmqcQ&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=2
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Probability and Statistics - https://www.youtube.com/watch?v=Mi8wnYc1m04&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=3
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Linear Algebra - https://www.youtube.com/watch?v=lNHaZlZJATw&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=4
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Perceptron and Logistic Regression - https://www.youtube.com/watch?v=WViuTuAOPlM&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=5
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Exponential Family and GLMs - https://www.youtube.com/watch?v=sj0iPn03i7Q&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=6
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GDA, Naive and Laplace Smoothing - https://www.youtube.com/watch?v=yieIOW9Kaw4&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=7
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Kernel Methods and SVMs - https://www.youtube.com/watch?v=p61QzJakQxg&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=8
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Bayesian Methods and Parametric and non parametric models - https://www.youtube.com/watch?v=IgUi7BDe1DQ&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=9
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Deep learning 1 - https://www.youtube.com/watch?v=mpJ2bFF6o8s&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=10
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Deep learning 2 - https://www.youtube.com/watch?v=4wmqDaFhs9E&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=11
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Bias and Variance regularization - https://www.youtube.com/watch?v=XhyOAX6oSX4&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=12
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Statistical Learning Theory & Uniform Convergence - https://www.youtube.com/watch?v=AbhV49lfaWw&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=13
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Reinforcement Learning 1 - https://www.youtube.com/watch?v=jNevGGOkklE&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=14
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Reinforcement Learning 2 - https://www.youtube.com/watch?v=4BbHU2_wphg&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=15
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K-Means and EM and GMM - https://www.youtube.com/watch?v=LmpkKwsyQj4&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=16
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Factor Analysis and Elbo - https://www.youtube.com/watch?v=pA-bo8_HNy4&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=17
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Principal and Independent Component Analysis - https://www.youtube.com/watch?v=7pJ6XNvpO8M&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=18
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Maximum entropy and calibration - https://www.youtube.com/watch?v=i6d5QTmPXiw&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=19
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Variational Autoencoders (VAEs) - https://www.youtube.com/watch?v=-TPFg-RG-KY&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=20
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Evaluation Metrics - https://www.youtube.com/watch?v=Lb1-iNIOLBw&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=21
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Practical Tips and Course recaps - https://www.youtube.com/watch?v=OftHZYlrK-E&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=22
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Course recap and wrap up - [https://www.youtube.com/watch?v=-uzSvC5m60&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=23](https://www.youtube.com/watch?v=-uzSvC5m60&list=PLoROMvodv4rNH7qL6-efu_q2_bPuy0adh&index=23)