投稿

【深度学习】李宏毅Machine Learning (2017,秋，台湾大学) 国语

10.5万

1008

2017-10-31 12:44:25

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

私は永遠に芽衣が好き发消息

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

顶部