Lecture 4 - Perceptron & Generalized Linear Model | Stanford CS229: Machine Learning (Autumn 2018)

Published 2020-04-17

Download video MP4 360p

Recommendations

Similar videos

1:17:25

Stanford CS229 Machine Learning I Exponential family, Generalized Linear Models I 2022 I Lecture 4
1:20:14

Lecture 11 - Introduction to Neural Networks | Stanford CS229: Machine Learning (Autumn 2018)
1:12:43

RL Debugging and Diagnostics | Stanford CS229: Machine Learning Andrew Ng - Lecture 20 (Autumn 2018)
1:20:41

Lecture 10 - Decision Trees and Ensemble Methods | Stanford CS229: Machine Learning (Autumn 2018)
1:16:38

Lecture 12 - Backprop & Improving Neural Networks | Stanford CS229: Machine Learning (Autumn 2018)
1:19:34

Locally Weighted & Logistic Regression | Stanford CS229: Machine Learning - Lecture 3 (Autumn 2018)
1:18:10

Lecture 16 - Independent Component Analysis & RL | Stanford CS229: Machine Learning (Autumn 2018)
1:20:15

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

Lecture 9 - Approx/Estimation Error & ERM | Stanford CS229: Machine Learning (Autumn 2018)
1:20:31

Lecture 14 - Expectation-Maximization Algorithms | Stanford CS229: Machine Learning (Autumn 2018)
1:18:55

Lecture 13 - Debugging ML Models and Error Analysis | Stanford CS229: Machine Learning (Autumn 2018)
1:52:47

Stanford CS229: Machine Learning | Summer 2019 | Lecture 5 - Perceptron and Logistic Regression
1:23:26

Lecture 8 - Data Splits, Models & Cross-Validation | Stanford CS229: Machine Learning (Autumn 2018)
1:20:57

Lecture 6 - Support Vector Machines | Stanford CS229: Machine Learning Andrew Ng (Autumn 2018)
More results