Part 1. Introduction

Part 1 introduces the history of deep learning, relating it to other forms of machine learning–based natural language processing (NLP; chapter 1). Chapter 2 discusses the basic architectures of deep learning for NLP and their implementation in Keras. Chapter 3 discusses how to represent text for deep learning using embeddings and focuses on Word2Vec and Doc2Vec, two popular embedding strategies.