李宏毅机器学习(2017)
src: https://www.youtube.com/playlist?list=PLJV_el3uVTsPy9oCRY30oBPNLCo89yu49
Home: http://speech.ee.ntu.edu.tw/~tlkagk/courses_ML17.html
视频选集
（30/40）
0-1: Introduction of Machine Learning
38:57
0-2: Why we need to learn machine learning?
01:20
1: Regression - Case Study
01:25:57
1- Regression - Demo - YouTube (HD)
06:53
2: Where does the error come from?
43:14
3-1: Gradient Descent
01:01:52
3-2- Gradient Descent (Demo by AOE)
02:35
3-3- Gradient Descent (Demo by Minecraft)
01:40
HW1 – PM2.5 Prediction
14:06
4: Classification
01:09:41
5: Logistic Regression
01:09:09
HW2 - Winner or Loser
03:21
6: Brief Introduction of Deep Learning
46:32
7: Backpropagation
20:20
8-1: “Hello world” of deep learning
29:51
8-2- Keras 2.0
09:37
8-3- Keras Demo
11:13
9-1: Tips for Training DNN
01:22:35
9-2- Keras Demo 2
15:21
9-3- Fizz Buzz in Tensorflow (sequel)
06:10
10: Convolutional Neural Network
01:23:26
11: Why Deep?
57:46
12: Semi-supervised
01:00:00
13: Unsupervised Learning - Linear Methods
01:40:24
14: Unsupervised Learning - Word Embedding
42:10
15: Unsupervised Learning - Neighbor Embedding
30:29
16: Unsupervised Learning - Auto-encoder
36:52
17- Unsupervised Learning - Deep Generative Model (Part I)
29:34
18- Unsupervised Learning - Deep Generative Model (Part II)
01:03:31
19: Transfer Learning
01:11:26
20- Support Vector Machine (SVM)
01:05:26
21- Structured Learning - Introduction
19:32
22- Structured Learning - Linear Model
24:15
23- Structured Learning - Structured SVM
02:11:44
24- Structured Learning - Sequence Labeling
01:43:31
25: Recurrent Neural Network (Part I)
49:01
26: Recurrent Neural Network (Part II)
01:30:56
27: Ensemble
01:40:02
28- Deep Reinforcement Learning - Scratching the surface
01:06:21
The Next Step for Machine Learning
15:27
顶部