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Stanford Online

@stanfordonline · 21 tutorials here

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1:20:14

Lecture 10 – Introduction to Neural Networks | Stanford CS229: Machine Learning (Autumn 2018)
Stanford Online
307.2K views
1:16:38

Lecture 11 – Backprop & Improving Neural Networks | Stanford CS229: Machine Learning (Autumn 2018)
Stanford Online
135.9K views
1:18:55

Lecture 12 – Debugging ML Models and Error Analysis | Stanford CS229: Machine Learning (Autumn 2018)
Stanford Online
123.2K views
1:20:31

Lecture 13 – Expectation-Maximization Algorithms | Stanford CS229: Machine Learning (Autumn 2018)
Stanford Online
205.6K views
1:19:48

Lecture 14 – EM Algorithm & Factor Analysis | Stanford CS229: Machine Learning Andrew Ng -Autumn2018
Stanford Online
97.3K views
1:18:35

Lecture 15 – PCA and ICA | Stanford CS229: Machine Learning Andrew Ng – Autumn 2018
Stanford Online
14K views
1:18:10

Lecture 16 – Independent Component Analysis & RL | Stanford CS229: Machine Learning (Autumn 2018)
Stanford Online
100.1K views
1:19:14

Lecture 17 – MDPs & Value/Policy Iteration | Stanford CS229: Machine Learning Andrew Ng (Autumn2018)
Stanford Online
119.8K views
1:20:15

Lecture 18 – Continous State MDP & Model Simulation | Stanford CS229: Machine Learning (Autumn 2018)
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66K views
1:26:03

Discussion Section: Learning Theory | Stanford CS229: Machine Learning (Autumn 2018)
Stanford Online
125.7K views
1:21:07

Lecture 19 – Reward Model & Linear Dynamical System | Stanford CS229: Machine Learning (Autumn 2018)
Stanford Online
83K views
1:20:41

Lecture 9 – Decision Trees and Ensemble Methods | Stanford CS229: Machine Learning (Autumn 2018)
Stanford Online
258.4K views
1:12:43

RL Debugging and Diagnostics | Stanford CS229: Machine Learning Andrew Ng – Lecture 20 (Autumn 2018)
Stanford Online
87.3K views
1:15:20

Stanford CS229: Machine Learning Lecture 1 – Andrew Ng (Autumn 2018)
Stanford Online
4.7M views
1:18:17

Stanford CS229: Machine Learning – Linear Regression and Gradient Descent | Lecture 2 (Autumn 2018)
Stanford Online
2.1M views
1:19:34

Locally Weighted & Logistic Regression | Stanford CS229: Machine Learning – Lecture 3 (Autumn 2018)
Stanford Online
902.4K views
1:22:02

Lecture 4 – Perceptron & Generalized Linear Model | Stanford CS229: Machine Learning (Autumn 2018)
Stanford Online
469.2K views
1:18:52

Lecture 5 – GDA & Naive Bayes | Stanford CS229: Machine Learning Andrew Ng (Autumn 2018)
Stanford Online
420.7K views
1:20:57

Lecture 6 – Support Vector Machines | Stanford CS229: Machine Learning Andrew Ng (Autumn 2018)
Stanford Online
368.2K views
1:20:25

Lecture 7 – Kernels | Stanford CS229: Machine Learning Andrew Ng (Autumn 2018)
Stanford Online
268.7K views
1:23:26

Lecture 8 – Data Splits, Models & Cross-Validation | Stanford CS229: Machine Learning (Autumn 2018)
Stanford Online
185.6K views