個人技術棧構建

Tasks

2019 tasks

• CS224n
• DL Book and CS230
• David Silver RL and CS234
• Tensorflow: https://github.com/aymericdamien/TensorFlow-Examples

2020 tasks

• Jacob NLP and slp
• DRL
• PRML

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Resources

Deep Learning

• Ian Goodfellow. Deep Learning Book
• CS230 Deep Learning

Natural Language Processing

• Dan Jurafsky. Speech and Language Processing (3rd)
• Jacob Eisenstein. Natural Language Processing
• CS224n: Natural Language Processing with Deep Learning

Reinforcement Learning

• David Silver. Course on Reiforcement Learning
• CS234: Reinforcement Learning Winter 2019
• Deep Reinforcement Learning: An Overview
• Spinning Up in Deep RL produced by OpenAI

Machine Learning

• 李航. 《統計學習方法》
• Christopher Bishop. Pattern Recognition and Machine Learning

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Natural Language Processing 學習

學完要畫一張nlp腦圖

Topic	cs224n	slp3	others
nlp basics: math and optimizers	lecture 0
Word Vectors	lecture 1: Introduction and Word Vectors lecture 2: Word Vectors 2 and Word Senses	chapter 6: Vector Semantics	ruder.io/word-embeddings
Neural Networks	lecture 3: Word Window Classification, Neural Networks, and Matrix Calculus lecture 4: Backpropagation and Computation Graphs	chapter 7: Neural Networks and Neural LM	Neural Networks and Deep Learning
Dependency Parsing	lecture 5: Linguistic Structure: Dependency Parsing	chapter 8: Part-of-Speech Tagging
RNN	lecture 6: Recurrent Neural Networks and Language Models lecture 7: Vanishing Gradients, Fancy RNNs		Recurrent Neural Networks Tutorial, Part 1–Introduction to RNNs Understanding LSTM Networks The Unreasonable Effectiveness of Recurrent Neural Networks
NMT	lecture 8: Machine Translation, Seq2Seq and Attention		https://github.com/tensorflow/nmt https://arxiv.org/abs/1703.01619
Assignments 3	midterm 3 practice	midterm test
ELMO
	Lecture12: Transformer Networks and CNNs
	Lecture15: Advanced Architectures and Memory Networks
Transformer -> Bert
9		Lecture17: Semi-supervised Learning for NLP