“Practical Natural Language Processing”
This book presents a complete look on constructing real world NLP applications. it covers the whole lifecycle of a typical NLP project – right from data gathering to installing and monitoring the model. While some of these processes are highly particular to NLP, others can be used to any ML pipeline. In order to create an NLP system from scratch, the book also offers task-specific case studies and domain-specific instructions.
Why should one learn from this book?
- It covers Text representation
- Most common NLP tasks such as classification, entity recognition, knowledge dissemination
- Tasks which involve cross engineering expertise such as social media mining etc.
- Explicable AI where they show how-to explain the decision of a classifier; working with limited data.
Authors: Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana
Top Natural Language Processing (NLP) Books
It is important to understand both theoretical foundations and practical applications when it comes to NLP. There are many books available that cover all the key concepts, methods, and tools you need. Whether you are a beginner or a professional, choosing the right book can be challenging.
In this article, we will look at some Top NLP books, Why they are unique, and why you should read them.
Table of Content
- Top 7 Natura Language Books(NLP) Books
- 1. Practical Natural Language Processing
- 2. Speech and Language Processing
- 3. Foundations of Statistical Natural Language Processing
- 4. Neural Network Methods in Natural Language Processing
- 5. Natural Language Understanding
- 6. Natural Language Processing with Python
- 7. Natural Language Processing in Action
- Additional NLP Books to Consider