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李宏毅2020机器学习深度学习(完整版)国语

235.7万

4.5万

2020-03-08 00:24:26

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MACHINELEARNING

大佬的迷弟的粉丝发消息

致力于划水摸鱼的佛系研究生

世纪辐射【上】

112.6万 1.5万

机器学习

37:08

Rule of ML 2020

22:04

Regression - Case Study

01:18:35

Basic Concept

43:14

Gradient Descent_1

01:01:52

Gradient Descent_2

02:36

Gradient Descent_3

01:41

Optimization for Deep Learning (1_2) (选学)

54:36

Optimization for Deep Learning (2_2) (选学)

54:32

Classification_1

01:09:41

Logistic Regression

01:07:13

Brief Introduction of Deep Learning

46:30

Backpropagation

31:26

Tips for Training DNN

01:26:02

Why Deep-

57:45

PyTorch Tutorial

52:39

Convolutional Neural Network

01:19:29

Graph Neural Network (1_2) (选学)

39:02

Graph Neural Network (2_2) (选学)

01:11:37

Recurrent Neural Network (Part I)

49:00

Recurrent Neural Network (Part II)

01:30:50

Semi-supervised

59:59

Unsupervised Learning - Word Embedding

40:39

Explainable ML (1_8)

13:51

Explainable ML (2_8)

14:08

Explainable ML (3_8)

06:08

Explainable ML (4_8)

07:16

Explainable ML (5_8)

08:13

Explainable ML (6_8)

07:27

Explainable ML (7_8)

08:03

Explainable ML (8_8)

07:17

More about Explainable AI (选学)

01:44:29

Attack ML Models (1_8)

06:06

Attack ML Models (2_8)

11:43

Attack ML Models (3_8)

07:03

Attack ML Models (4_8)

08:12

Attack ML Models (5_8)

06:39

Attack ML Models (6_8)

09:27

Attack ML Models (7_8)

08:04

Attack ML Models (8_8)

10:11

More about Adversarial Attack (1_2) (选学)

29:58

More about Adversarial Attack (2_2) (选学)

29:45

Network Compression (1_6)

08:24

Network Compression (2_6)

12:44

Network Compression (3_6)

08:33

Network Compression (4_6)

06:37

Network Compression (5_6)

11:53

Network Compression (6_6)

13:09

Network Compression (1_2) - Knowledge Distillation (选学)

01:07:53

Network Compression (2_2) - Network Pruning (选学)

39:33

Conditional Generation by RNN & Attention

01:41:14

Pointer Network

13:34

Recursive

24:58

Transformer

49:32

Transformer and its variant (选学)

01:49:23

Unsupervised Learning - Linear Methods

01:40:20

Unsupervised Learning - Neighbor Embedding

30:58

Unsupervised Learning - Auto-encoder

42:04

More about Auto-encoder (1_4)

13:39

More about Auto-encoder (2_4)

06:12

More about Auto-encoder (3_4)

12:29

More about Auto-encoder (4_4)

14:52

ELMO, BERT, GPT

01:04:52

Self-supervised Learning (选学)

40:37

Anomaly Detection (1_7)

13:23

Anomaly Detection (2_7)

14:10

Anomaly Detection (3_7)

14:05

Anomaly Detection (4_7)

04:08

Anomaly Detection (6_7)

12:20

Anomaly Detection (7_7)

06:02

More about Anomaly Detection (选学)

46:52

Generative Adversarial Network(1_10)

01:33:15

Generative Adversarial Network(2_10)

26:19

Generative Adversarial Network(3_10)

38:59

Generative Adversarial Network(4_10)

01:20:19

Generative Adversarial Network(5_10)

25:04

Generative Adversarial Network(6_10)

50:07

Generative Adversarial Network(7_10)

46:03

Generative Adversarial Network(8_10)

22:46

Generative Adversarial Network(9_10)

01:27:23

Generative Adversarial Network(10_10)

30:09

SAGAN, BigGAN, SinGAN, GauGAN, GANILLA, NICE-GAN（选学）

01:06:17

Transfer Learning

01:14:28

More about Domain Adaptation (1_2) (选学)

52:01

More about Domain Adaptation (2_2) (选学)

34:11

Meta Learning – MAML (1_9)

07:42

Meta Learning – MAML (2_9)

07:53

Meta Learning – MAML (3_9)

10:21

Meta Learning – MAML (4_9)

05:15

Meta Learning – MAML (5_9)

13:22

Meta Learning – MAML (6_9)

06:33

Meta Learning – MAML (7_9)

08:54

Meta Learning – MAML (8_9)

05:12

Meta Learning – MAML (9_9)

06:53

Meta Learning - Gradient Descent as LSTM (1_3)

11:40

Meta Learning - Gradient Descent as LSTM (2_3)

10:06

Meta Learning - Gradient Descent as LSTM (3_3)

10:39

More about Meta Learning (选学)

44:10

More about Meta Learning (选学)

53:11

Life Long Learning (1_7)

13:51

Life Long Learning (2_7)

07:25

Life Long Learning (3_7)

12:04

Life Long Learning (4_7)

04:40

Life Long Learning (5_7)

03:20

Life Long Learning (6_7)

14:15

Life Long Learning (7_7)

11:35

More about Lifelong Learning (选学)

57:48

Deep Reinforcemen Learning(3_1)

01:06:22

Deep Reinforcemen Learning(3_2)

13:20

Deep Reinforcemen Learning(3_3)

01:05:34

RL Advanced Version_1_Policy Gradient

45:49

RL Advanced Version_2_ Proximal Policy Optimization

41:34

RL Advanced Version_3_Q-Learning

49:44

RL Advanced Version_4_Q-Learning Advanced Tips

38:31

RL Advanced Version_5_Q-Learning Continuous Action

14:58

RL Advanced Version_6_Actor-Critic

34:16

RL Advanced Version_7_Sparse Reward

30:16

RL Advanced Version_8_Imitation Learning

34:02

RL - Model-based, Large-scale, Meta, Multi-agent, Hide-and-seek, Alpha（选学）

01:42:05

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