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studynotes_cs224n

This repository is created for sharing study notes for the nlp class cs224n

【content】

prerequisite: 

- linear algebra review

- probability theorem review

- convex optimization review

week 1: word2vec, skip-gram

- lecture 1: class introduction

- lecture 2: word2vec

- word2vec tutorial: skip gram neural network architecture for Word2Vec

- lecture notes01: Natural Language Processing. Word Vectors. Singular Value Decomposition. Skip-gram. Continuous Bag of Words (CBOW). Negative Sampling. Hierarchical Softmax. Word2Vec

- paper: Distributed Representations ofWords and Phrases and their Compositionality: subsampling, negative sampling, method for finding phrases

- paper: Efficient Estimation of Word Representations in Vector Space: dealing with large data set, achieving large improvements in accuracy at much lower computational cost


week 2: GloVe, word vector evaluation

- lecture 3: finish word2vec, GloVe intro

- lecture notes02: GloVe, evaluation, Window classification

- paper: GloVe_Global Vectors for Word Representation

- paper: Evaluation methods for unsupervised word embeddings

- paper: Improving Distributional Similarity with Lessons Learned from Word Embeddings


week 3: classification, backward propagation

- lecture 4: classification

- lecture 5: multi-layer NN, backward propagation

- lecture notes03: Neural networks. Forward computation. Backward propagation. 

- gradient notes: Computing Neural Network Gradients

- paper: review-differential-calculus

- paper: Natural Language Processing (almost) from Scratch

- paper: backprop_old


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