(强推|双字)2018秋季CS229机器学习-官方高清版

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开始看视频前先看Up下面这段话: 1.这是2018版的机器学习视频,上一次公开是2008版的。 2.地址:http://cs229.stanford.edu/syllabus.html 3.不定期分享高质量人工智能视频,关注点赞和Up一起学习啦。
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Lecture 1 - Stanford CS229- Machine Learning - Andrew Ng (Autumn 2018)
01:15:20
Lecture 2 - Linear Regression and Gradient Descent
01:18:17
Lecture 3 - Locally Weighted & Logistic Regression
01:19:35
Lecture 4 - Perceptron & Generalized Linear Model
01:22:02
Lecture 5 - GDA & Naive Bayes
01:18:52
Lecture 6 - Support Vector Machines
01:20:57
Lecture 7 - Kernels
01:20:25
Lecture 8 - Data Splits, Models & Cross-Validation
01:23:26
Lecture 9 - Approx_Estimation Error _ ERM
01:26:03
Lecture 10 - Decision Trees and Ensemble Methods
01:20:41
Lecture 11 - Introduction to Neural Networks
01:20:14
Lecture 12 - Backprop _ Improving Neural Networks
01:16:38
Lecture 13 - Debugging ML Models and Error Analysis
01:18:55
Lecture 14 - Expectation-Maximization Algorithms
01:20:32
Lecture 15 - EM Algorithm _ Factor Analysis
01:19:48
Lecture 16 - Independent Component Analysis _ RL
01:18:10
Lecture 17 - MDPs & Value_Policy Iteration
01:19:15
Lecture 18 - Continous State MDP _ Model Simulation
01:20:15
Lecture 19 - Reward Model _ Linear Dynamical System
01:21:07
Lecture 20 - RL Debugging and Diagnostics
01:12:43
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