【李宏毅】2020 最新课程 (完整版) Machine Learning (2020)

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2020-03-08 19:21:50
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http://speech.ee.ntu.edu.tw/~tlkagk/courses_ML20.html 李宏毅最新 2020 机器学习课程; 按照作业方式编排; 中文绝佳的 ML/DL 入门课程; 包含目前热门技术等。
观世人如一人,合万念成一念。
视频选集
(11/81)
课程介绍 Machine Learning (2020) - Course Introduction-c9TwBeWAj_U
36:10
助教 Rule of ML 2020-Bms0Fnol5nE
22:04
作業一 ML Lecture 1 - Regression - Case Study-fegAeph9UaA
01:18:36
ML Lecture 2 - Where does the error come from-D_S6y0Jm6dQ
43:15
(Gradient Descent) 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
作業二 ML Lecture 4 - Classification-fZAZUYEeIMg
01:09:41
ML Lecture 5 - Logistic Regression-hSXFuypLukA
01:07:14
DL預備 ML Lecture 6 - Brief Introduction of Deep Learning-Dr-WRlEFefw
46:31
ML Lecture 7 - Backpropagation-ibJpTrp5mcE
31:26
ML Lecture 9-1 - Tips for Training DNN-xki61j7z-30
01:26:03
ML Lecture 9-2 - Keras Demo 2-Ky1ku1miDow
15:21
ML Lecture 9-3 - Fizz Buzz in Tensorflow (sequel)-F1vek6ULo9w
06:10
作業三 ML Lecture 10 - Convolutional Neural Network-FrKWiRv254g
01:19:29
作業四 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
作業五 Explainable ML (1_8)-lnjrn3bF9lA
13:51
Explainable ML (2_8)-pNpk6DPYUh8
14:08
Explainable ML (3_8)-K6TpPWLc52c
06:08
Explainable ML (4_8)-yORbWn7UsBs
07:15
Explainable ML (5_8)-1xnhQbAV1m0
08:13
Explainable ML (6_8)-K1mWgthGS-A
07:27
Explainable ML (7_8)-OjqIVSwly4k
08:03
Explainable ML (8_8)-gotiBlOu18I
07:16
作業六 Attack ML Models (1_8)-NI6yb0WgMBM
06:06
Attack ML Models (2_8)-zOdg05BwE7I
11:42
Attack ML Models (3_8)-F9N5zF7N0qY
07:04
Attack ML Models (4_8)-qjnMoWmn1FQ
08:12
Attack ML Models (5_8)-2mgLPZJOHNk
06:39
Attack ML Models (6_8)-z2nmPDLEXI0
09:27
Attack ML Models (7_8)-KH48zq2RfBA
08:04
Attack ML Models (8_8)-ah_Ttx6cIVU
10:11
作業七 Network Compression (1_6)-dPp8rCAnU_A
08:24
Network Compression (2_6)-7B8Cx7woQk4
12:44
Network Compression (3_6)-mzZzn8fBvEs
08:33
Network Compression (4_6)-fMsNf0ufYnY
06:37
Network Compression (5_6)-L0TOXlNpCJ8
11:53
Network Compression (6_6)-f0rOMyZSZi4
13:08
作業八 Conditional Generation by RNN & Attention-f1KUUz7v8g4
01:41:15
作業九 ML Lecture 13 - Unsupervised Learning - Linear Methods-iwh5o_M4BNU
01:40:21
ML Lecture 15 - Unsupervised Learning - Neighbor Embedding-GBUEjkpoxXc
30:59
ML Lecture 16 - Unsupervised Learning - Auto-encoder-Tk5B4seA-AU
42:04
作業十 Anomaly Detection (1_7)-gDp2LXGnVLQ
13:23
Anomaly Detection (2_7)-cYrNjLxkoXs
14:10
Anomaly Detection (3_7)-ueDlm2FkCnw
14:05
Anomaly Detection (4_7)-XwkHOUPbc0Q
04:07
Anomaly Detection (5_7)-Fh1xFBktRLQ
12:18
Anomaly Detection (6_7)-LmFWzmn2rFY
12:20
Anomaly Detection (7_7)-6W8FqUGYyDo
06:02
作業十一 GAN Lecture 1 (2018) - Introduction-DQNNMiAP5lw
01:33:15
GAN Lecture 2 (2018) - Conditional Generation-LpyL4nZSuqU
26:19
GAN Lecture 3 (2018) - Unsupervised Conditional Generation--3LgL3NXLtI
38:59
GAN Lecture 4 (2018) - Basic Theory-DMA4MrNieWo
01:20:19
GAN Lecture 5 (2018) - General Framework-av1bqilLsyQ
25:05
GAN Lecture 6 (2018) - WGAN, EBGAN-3JP-xuBJsyc
50:07
GAN Lecture 7 (2018) - Info GAN, VAE-GAN, BiGAN-sU5CG8Z0zgw
46:03
GAN Lecture 8 (2018) - Photo Editing-Lhs_Kphd0jg
22:46
GAN Lecture 9 (2018) - Sequence Generation-Xb1x4ZgV6iM
01:27:24
GAN Lecture 10 (2018) - Evaluation & Concluding Remarks-IB_ADssBomk
30:09
作業十二 ML Lecture 12 - Semi-supervised-fX_guE7JNnY
01:00:00
ML Lecture 19 - Transfer Learning-qD6iD4TFsdQ
01:14:29
作業十三Introduction of Meta Learning (for Interspeech 2020 Special Session webpage)
02:19:08
作業十四 Life Long Learning (1_7)-7qT5P9KJnWo
13:51
Life Long Learning (2_7)-X7aWP6LngEs
07:25
Life Long Learning (3_7)-8uo3kJ509hA
12:04
Life Long Learning (4_7)-UgLx4rjcCO8
04:40
Life Long Learning (5_7)-W37WANBMUTM
03:19
Life Long Learning (6_7)-D4aN7urRp3E
14:15
Life Long Learning (7_7)-CubL463rhsQ
11:35
作業十五 ML Lecture 23-1 - Deep Reinforcement Learning-W8XF3ME8G2I
01:06:22
ML Lecture 23-2 - Policy Gradient (Supplementary Explanation)-y8UPGr36ccI
13:21
ML Lecture 23-3 - Reinforcement Learning (including Q-learning)-2-JNBzCq77c
01:05:34
DRL Lecture 1 - Policy Gradient (Review)-z95ZYgPgXOY
45:49
DRL Lecture 2 - Proximal Policy Optimization (PPO)-OAKAZhFmYoI
41:34
DRL Lecture 3 - Q-learning (Basic Idea)-o_g9JUMw1Oc
49:44
DRL Lecture 4 - Q-learning (Advanced Tips)-2-zGCx4iv_k
38:31
DRL Lecture 5 - Q-learning (Continuous Action)-tnPVcec22cg
14:58
DRL Lecture 6 - Actor-Critic-j82QLgfhFiY
34:16
DRL Lecture 7 - Sparse Reward--5cCWhu0OaM
30:16
DRL Lecture 8 - Imitation Learning-rl_ozvqQUU8
34:02
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