【深度学习】李宏毅Machine Learning (2017,秋，台湾大学) 国语
https://www.youtube.com/channel/UC2ggjtuuWvxrHHHiaDH1dlQ
2017年秋季台湾大学李宏毅老师的机器学习视频。最新版，目前更新至第17课。
http://speech.ee.ntu.edu.tw/~tlkagk/courses_ML17_2.html
视频选集
（33/36）
ML Lecture 0-1 - Introduction of Machine Learning 机器学习简介
38:57
ML Lecture 0-2 - Why we need to learning machine learning 为什么要学习机器学习
01:20
ML Lecture 1 - Regression - Case Study 回归学习案例
01:18:34
ML Lecture 1 - Regression - Demo
06:53
ML Lecture 2 - Where does the error come from-误差来源
43:13
ML Lecture 3-1 - Gradient Descent-梯度下降
01:01:51
HW1 – PM2.5 Prediction-作业1
14:06
ML Lecture 4 - Classification-分类
01:09:40
ML Lecture 5 - Logistic Regression-逻辑回归
01:07:13
ML Lecture 6 - Brief Introduction of Deep Learning-深度学习简介
46:29
ML Lecture 7 - Backpropagation-反向传播
31:26
ML Lecture 8-1 - “Hello world” of deep learning
29:50
HW2 - Winner or Loser-作业2
03:21
ML Lecture 8-2 - Keras 2.0
09:37
ML Lecture 8-3 - Keras Demo
11:13
ML Lecture 9 - Tips for Training DNN-训练DNN的几点建议
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-卷积神经网络
01:19:29
ML Lecture 11 - Why Deep
57:45
ML Lecture 12.1 - Recurrent Neural Network (Part I)
48:59
ML Lecture 12.2 - Recurrent Neural Network (Part II)
01:30:49
ML Lecture 12 - Gated RNN and Sequence Generation
01:59:52
ML Lecture 13 - Ensemble 集成学习
01:39:59
ML Lecture 14 - Semi-supervised - 半监督学习
59:59
ML Lecture 15 - Transfer Learning - 迁移学习
01:14:28
ML Lecture 16 - Deep Reinforcement Learning - Scratching the surface - 深度强化学习的皮毛
01:06:21
ML Lecture 17 - Structured Learning - Linear Model-降维
24:15
ML Lecture 18 - Unsupervised Learning - Word Embedding
40:39
ML Lecture 19 - Unsupervised Learning - Neighbor Embedding
30:57
ML Lecture 20.1 - Gated RNN and Sequence Generation (Recorded at Fall, 2017)
01:59:52
ML Lecture 20.2 - Pointer Network
13:34
ML Lecture 21 - Unsupervised Learning - Auto-encoder
42:03
ML Lecture 22.1 - Unsupervised Learning - Deep Generative Model (Part I)
29:34
ML Lecture 22.2 - Unsupervised Learning - Deep Generative Model (Part II)
01:03:31
附加：Batch Normalization
28:57
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