Lecture 2 From BoW to Word2Vec

In-class Material

1. Slides

2. Notebook

Extra Reading

1. Gensim Introduction

2. Word2Vec Lecture by Chris Manning

3. Visualization for graphs of nearest neighbors from high-dimensional word2vec embeddings

4. Graph Embeddings

5. Natural Language Processing: From Basics to using RNN and LSTM

6. An Overview of the main concepts of Word2Vec, GloVe, and FastText

7. NLP Learning Series

8. Transfer Learning in NLP