文件	时间	大小	操作
	Lecture 01 Introduction and Word Vectors 2022-09-03 10:56:40
	Lecture 02 Word Vectors 2 and Word Senses 2022-09-03 10:56:40
	Lecture 03 Word Window Classification, Neural Networks, and Matrix Calculus 2022-09-03 10:56:40
	Lecture 04 Backpropagation and Computation Graphs 2022-09-03 10:56:40
	Lecture 05 Linguistic Structure Dependency Parsing 2022-09-03 10:56:40
	Lecture 06 The probability of a sentence Recurrent Neural Networks and Language Models 2022-09-03 10:56:40
	Lecture 07 Vanishing Gradients and Fancy RNNs 2022-09-03 10:56:40
	Lecture 08 Machine Translation, Seq2Seq and Attention 2022-09-03 10:56:40
	Lecture 09 Practical Tips for Final Projects 2022-09-03 10:56:40
	Lecture 10 Question Answering and the Default Final Project 2022-09-03 10:56:40
	Lecture 11 ConvNets for NLP 拼课加微信，zszhp2019 2022-09-03 10:56:40
	Lecture 12 Information from parts of words Subword Models 2022-09-03 10:56:40
	Lecture 13 Modeling contexts of use Contextual Representations and Pretraining 2022-09-03 10:56:40
	Lecture 14 Transformers and Self-Attention For Generative Models 2022-09-03 10:56:40
	Lecture 15 Natural Language Generation 2022-09-03 10:56:40
	Lecture 16 Reference in Language and Coreference Resolution 2022-09-03 10:56:40
	Lecture 18 Constituency Parsing and Tree Recursive Neural Networks 2022-09-03 10:56:40
	Lecture 19 Safety, Bias, and Fairness 2022-09-03 10:56:40
	Lecture 20 Future of NLP + Deep Learning 2022-09-03 10:56:40