Applied Natural Language Processing with Python: Implementing Machine Learning and Deep Learning Algorithms for Natural Language Processing
Learn to harness the power of AI for natural language processing, performing tasks such as spell check, text summarization, document classification, and natural language generation. Along the way, you will learn the skills to implement these methods in larger infrastructures to replace existing code or create new algorithms.
Applied Natural Language Processing with Python starts with reviewing the necessary machine learning concepts before moving onto discussing various NLP problems. After reading this book, you will have the skills to apply these concepts in your own professional environment.
What You Will Learn
- Utilize various machine learning and natural language processing libraries such as TensorFlow, Keras, NLTK, and Gensim
- Manipulate and preprocess raw text data in formats such as .txt and .pdf
- Strengthen your skills in data science by learning both the theory and the application of various algorithms
Who This Book Is For
You should be at least a beginner in ML to get the most out of this text, but you needn’t feel that you need be an expert to understand the content.
Table of Contents
Chapter 1: What Is Natural Language Processing?
Chapter 2: Review of Deep Learning
Chapter 3: Working with Raw Text
Chapter 4: Topic Modeling and Word Embeddings
Chapter 5: Text Generation, Machine Translation, and Other Recurrent Language Modeling Tasks