Playlist Duration

Playlist · Stanford Online

Stanford CS229: Machine Learning led by Andrew Ng | Autumn 2018

by Stanford Online · 21 videos

Listed in Best free machine learning courses on YouTube, ranked by total hours

Total watch time

1d 3h 52m

at 1× speed · exactly 1 day, 3 hours, 51 minutes, 47 seconds at 1×

At an hour a day you'd finish in 28 days

The shape of the course

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1:26:03

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About 28 days at an hour a day

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Videos (21)

1d 3h 52m in total · tick what you've watched

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Videos to
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1 Stanford CS229: Machine Learning Lecture 1 - Andrew Ng (Autumn 2018) 1:15:20 2020-04-17
2 Stanford CS229: Machine Learning - Linear Regression and Gradient Descent | Lecture 2 (Autumn 2018) 1:18:17 2020-04-17
3 Locally Weighted & Logistic Regression | Stanford CS229: Machine Learning - Lecture 3 (Autumn 2018) 1:19:34 2020-04-17
4 Lecture 4 - Perceptron & Generalized Linear Model | Stanford CS229: Machine Learning (Autumn 2018) 1:22:02 2020-04-17
5 Lecture 5 - GDA & Naive Bayes | Stanford CS229: Machine Learning Andrew Ng (Autumn 2018) 1:18:52 2020-04-17
6 Lecture 6 - Support Vector Machines | Stanford CS229: Machine Learning Andrew Ng (Autumn 2018) 1:20:57 2020-04-17
7 Lecture 7 - Kernels | Stanford CS229: Machine Learning Andrew Ng (Autumn 2018) 1:20:25 2020-04-17
8 Lecture 8 - Data Splits, Models & Cross-Validation | Stanford CS229: Machine Learning (Autumn 2018) 1:23:26 2020-04-17
9 Discussion Section: Learning Theory | Stanford CS229: Machine Learning (Autumn 2018) 1:26:03 2020-04-17
10 Lecture 9 - Decision Trees and Ensemble Methods | Stanford CS229: Machine Learning (Autumn 2018) 1:20:41 2020-04-17
11 Lecture 10 - Introduction to Neural Networks | Stanford CS229: Machine Learning (Autumn 2018) 1:20:14 2020-04-17
12 Lecture 11 - Backprop & Improving Neural Networks | Stanford CS229: Machine Learning (Autumn 2018) 1:16:38 2020-04-17
13 Lecture 12 - Debugging ML Models and Error Analysis | Stanford CS229: Machine Learning (Autumn 2018) 1:18:55 2020-04-17
14 Lecture 13 - Expectation-Maximization Algorithms | Stanford CS229: Machine Learning (Autumn 2018) 1:20:31 2020-04-17
15 Lecture 14 - EM Algorithm & Factor Analysis | Stanford CS229: Machine Learning Andrew Ng -Autumn2018 1:19:48 2020-04-17
16 Lecture 15 - PCA and ICA | Stanford CS229: Machine Learning Andrew Ng - Autumn 2018 1:18:35 2026-02-26
17 Lecture 16 - Independent Component Analysis & RL | Stanford CS229: Machine Learning (Autumn 2018) 1:18:10 2020-04-17
18 Lecture 17 - MDPs & Value/Policy Iteration | Stanford CS229: Machine Learning Andrew Ng (Autumn2018) 1:19:14 2020-04-17
19 Lecture 18 - Continous State MDP & Model Simulation | Stanford CS229: Machine Learning (Autumn 2018) 1:20:15 2020-04-17
20 Lecture 19 - Reward Model & Linear Dynamical System | Stanford CS229: Machine Learning (Autumn 2018) 1:21:07 2020-04-17
21 RL Debugging and Diagnostics | Stanford CS229: Machine Learning Andrew Ng - Lecture 20 (Autumn 2018) 1:12:43 2020-04-17
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