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机器学习-李宏毅(2019) Machine Learning

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2018-11-14 11:10:05

中文领域机器学习入门的典范课程。

计算机科学

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AI agent的死循环？还是千问打破僵局？

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ML Lecture 0 - Introduction of Machine Learning

38:57

ML Lecture 1 - Regression - Case Study

01:18:35

ML Lecture 1 - Regression - Demo

06:53

ML Lecture 2 - Where does the error come from

43:14

ML Lecture 3-1 - Gradient Descent

01:01:52

ML Lecture 3-2 - Gradient Descent (Demo by AOE)

02:36

ML Lecture 3-3 - Gradient Descent (Demo by Minecraft)

01:41

ML Lecture 4 - Classification

01:09:41

ML Lecture 5 - Logistic Regression

01:07:13

ML Lecture 6 - Brief Introduction of Deep Learning-Dr

46:30

ML Lecture 7 - Backpropagation

31:26

ML Lecture 8-1 - “Hello world” of deep learning

29:51

ML Lecture 8-2 - Keras 2.0

09:38

ML Lecture 8-3 - Keras Demo

11:14

ML Lecture 9-1 - Tips for Training DNN

01:26:02

ML Lecture 9-2 - Keras Demo 2

15:21

ML Lecture 9-3 - Fizz Buzz in Tensorflow (sequel)

06:10

ML Lecture 10 - Convolutional Neural Network

01:19:29

ML Lecture 11 - Why Deep

57:46

ML Lecture 12 - Semi-supervised

59:59

ML Lecture 13 - Unsupervised Learning - Linear Methods

01:40:20

ML Lecture 14 - Unsupervised Learning - Word Embedding

40:39

ML Lecture 15 - Unsupervised Learning - Neighbor Embedding

30:58

ML Lecture 16 - Unsupervised Learning - Auto-encoder

42:04

ML Lecture 17 - Unsupervised Learning - Deep Generative Model (Part I)

29:34

ML Lecture 18 - Unsupervised Learning - Deep Generative Model (Part II)

01:03:31

ML Lecture 19 - Transfer Learning

01:14:28

ML Lecture 20 - Support Vector Machine (SVM)

01:05:27

ML Lecture 21-1 - Recurrent Neural Network (Part I)

49:00

ML Lecture 21-2 - Recurrent Neural Network (Part II)

01:30:50

ML Lecture 22 - Ensemble

01:39:59

ML Lecture 23-1 - Deep Reinforcement Learning

01:06:22

ML Lecture 23-2 - Policy Gradient (Supplementary Explanation)

13:20

ML Lecture 23-3 - Reinforcement Learning (including Q-learning)

01:05:34

Structured Learning 1 - Introduction

19:33

Structured Learning 2 - Linear Model

24:15

Structured Learning 3 - Structured SVM

02:11:45

Structured Learning 4 - Sequence Labeling

01:43:31

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