台大《应用深度学习》

  • 名称:台大《应用深度学习》
  • 分类:人工智能  
  • 观看人数:加载中
  • 时间:2020/11/10 21:43:32
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Lecture 0 2019/02/19 Course Logistics [slides]


Registration: [Google Form]

Lecture 1 2019/02/26 Introduction [slides] (video)

Guest Lecture (R103) [PyTorch Tutorial]

Lecture 2 2019/03/05 Neural Network Basics [slides] (video)

Suggested Readings:

[Linear Algebra]

[Linear Algebra Slides]

[Linear Algebra Quick Review]

A1 2019/03/05 A1: Dialogue Response Selection [A1 pages]

Lecture 3 2019/03/12 Backpropagation [slides] (video)

Word Representation [slides] (video)

Suggested Readings:

[Learning Representations]

[Vector Space Models of Semantics]

[RNNLM: Recurrent Neural Nnetwork Language Model]

[Extensions of RNNLM]

[Optimzation]

Lecture 4 2019/03/19 Recurrent Neural Network [slides] (video)

Basic Attention [slides] (video)

Suggested Readings:

[RNN for Language Understanding]

[RNN for Joint Language Understanding]

[Sequence-to-Sequence Learning]

[Neural Conversational Model]

[Neural Machine Translation with Attention]

[Summarization with Attention]

[Normalization]

A2 2019/03/19 A2: Contextual Embeddings [A2 pages]

Lecture 5 2019/03/26 Word Embeddings [slides] (video)

Contextual Embeddings - ELMo [slides] (video)

Suggested Readings:

[Estimation of Word Representations in Vector Space]

[GloVe: Global Vectors for Word Representation]

[Sequence Tagging with BiLM]

[Learned in Translation: Contextualized Word Vectors]

[ELMo: Embeddings from Language Models]

[More Embeddings]

2019/04/02 Spring Break A1 Due

Lecture 6 2019/04/09 Transformer [slides] (video)


Contextual Embeddings - BERT [slides] (video)


Gating Mechanism [slides] (video)

Suggested readings:

[Contextual Word Representations Introduction]

[Attention is all you need]

[BERT: Pre-training of Bidirectional Transformers]

[GPT: Improving Understanding by Unsupervised Learning]

[Long Short-Term Memory]

[Gated Recurrent Unit]

[More Transformer]

Lecture 7 2019/04/16 Reinforcement Learning Intro [slides] (video)

Basic Q-Learning [slides] (video)

Suggested Readings:

[Reinforcement Learning Intro]

[Stephane Ross' thesis]

[Playing Atari with Deep Reinforcement Learning]

[Deep Reinforcement Learning with Double Q-learning]

[Dueling Network Architectures for Deep Reinforcement Learning]

A3 2019/04/16 A3: RL for Game Playing [A3 pages]

Lecture 8 2019/04/23 Policy Gradient [slides] (video)

Actor-Critic (video)

More about RL [slides] (video) Suggested Readings:

[Asynchronous Methods for Deep Reinforcement Learning]

[Deterministic Policy Gradient Algorithms]

[Continuous Control with Deep Reinforcement Learning]

A2 Due

Lecture 9 2019/04/30 Generative Adversarial Networks [slides] (video)

(Lectured by Prof. Hung-Yi Lee)

Lecture 10 2019/05/07 Convolutional Neural Networks [slides]

A4 2019/05/07 A4: Drawing [A4 pages]

2019/05/14 Break A3 Due

Lecture 11 2019/05/21 Unsupervised Learning [slides]

NLP Examples [slides]

Project Plan [slides]

Special 2019/05/28 Company Workshop Registration: [Google Form]

2019/06/04 Break A4 Due

Lecture 12 2019/06/11 Project Progress Presentation

Course and Career Discussion

Special 2019/06/18 Company Workshop Registration: [Google Form]

Lecture 13 2019/06/25 Final Presentation