Machine Learning-李宏毅教授最新版(2017,fall)

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2019-02-09 12:42:47
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https://www.youtube.com/playlist?list=PLJV_el3uVTsPy9oCRY30oBPNLCo89yu49 机器学习入门教程,可反复看,每一次都能学到新东西,建议倍速看这样可以防止瞌睡,大脑运转快。
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ML Lecture 0-1 - Introduction of Machine Learning-CXgbekl66jc
38:57
ML Lecture 1 - Regression - Case Study-fegAeph9UaA
01:18:35
ML Lecture 1 - Regression - Demo-1UqCjFQiiy0
06:53
ML Lecture 2 - Where does the error come from-D_S6y0Jm6dQ
43:14
ML Lecture 3-1 - Gradient Descent-yKKNr-QKz2Q
01:01:52
ML Lecture 3-2 - Gradient Descent (Demo by AOE)-1_HBTJyWgNA
02:36
ML Lecture 3-3 - Gradient Descent (Demo by Minecraft)-wzPAInDF_gI
01:41
ML Lecture 4 - Classification-fZAZUYEeIMg
01:09:41
ML Lecture 5 - Logistic Regression-hSXFuypLukA
01:07:13
ML Lecture 6 - Brief Introduction of Deep Learning-Dr-WRlEFefw
46:30
ML Lecture 7 - Backpropagation-ibJpTrp5mcE
31:26
ML Lecture 8-1 - “Hello world” of deep learning-Lx3l4lOrquw
29:51
ML Lecture 8-2 - Keras 2.0-5BJDJd-dzzg
09:37
ML Lecture 8-3 - Keras Demo-L8unuZNpWw8
11:14
ML Lecture 9-1 - Tips for Training DNN-xki61j7z-30
01:26:02
ML Lecture 9-2 - Keras Demo 2-Ky1ku1miDow
15:21
ML Lecture 9-3 - Fizz Buzz in Tensorflow (sequel)-F1vek6ULo9w
06:10
ML Lecture 10 - Convolutional Neural Network-FrKWiRv254g
01:19:29
ML Lecture 11 - Why Deep-XsC9byQkUH8
57:46
ML Lecture 12 - Semi-supervised-fX_guE7JNnY
59:59
ML Lecture 13 - Unsupervised Learning - Linear Methods-iwh5o_M4BNU
01:40:20
ML Lecture 14 - Unsupervised Learning - Word Embedding-X7PH3NuYW0Q
40:39
ML Lecture 15 - Unsupervised Learning - Neighbor Embedding-GBUEjkpoxXc
30:58
ML Lecture 16 - Unsupervised Learning - Auto-encoder-Tk5B4seA-AU
42:04
ML Lecture 17 - Unsupervised Learning - Deep Generative Model (Part I)-YNUek8ioA
29:34
ML Lecture 18 - Unsupervised Learning - Deep Generative Model (Part II)-8zomhgKr
01:03:31
ML Lecture 19 - Transfer Learning-qD6iD4TFsdQ
01:14:28
ML Lecture 20 - Support Vector Machine (SVM)-QSEPStBgwRQ
01:05:27
ML Lecture 21-1 - Recurrent Neural Network (Part I)-xCGidAeyS4M
49:00
ML Lecture 21-2 - Recurrent Neural Network (Part II)-rTqmWlnwz_0
01:30:50
ML Lecture 22 - Ensemble-tH9FH1DH5n0
01:39:59
ML Lecture 23-1 - Deep Reinforcement Learning-W8XF3ME8G2I
01:06:22
ML Lecture 23-2 - Policy Gradient (Supplementary Explanation)-y8UPGr36ccI
13:20
ML Lecture 23-3 - Reinforcement Learning (including Q-learning)-2-JNBzCq77c
01:05:34
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