“Foundations of Statistical Natural Language Processing”

The book contains all the theory and algorithms that you will ever need for building NLP tools. It broadly covers mathematical and linguistic foundations and also has statistical methods discussed in details. Thus, this book allows the students and researcher to construct their own implementations.

Why should one learn from this book?

  • Covers collocation finding and word sense disambiguation
  • Explains Probabilistic parsing , information retrieval, and other applications.

Authors: Christopher D. Manning and Hinrich Schütze

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.

Top Natural Language Processing (NLP) Books

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

Similar Reads

Top 7 Natura Language Books(NLP) Books

Natural Language Processing (NLP) is a booming field and an integral part of artificial intelligence and machine learning. It is dedicated to interaction between the computers and human languages. Thus, NLP enables machines to understand, interpret, and generate human language in a valuable way. The best book on NLP would be the one covering all the foundational concepts, core techniques and methodologies (like text preprocessing and statistical models), practical applications, and tools. It should have advanced topics that cover the recent advancement in the field and consideration of ethics and bias. Further, Hands-On Projects and problem sets can perfectly help to practice what you learn....

1. “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....

2. “Speech and Language Processing”

This book presents cutting-edge algorithms and methods for text-based and speech-based natural language processing, providing a cohesive view of speech and language processing. It discusses both statistical and symbolic approaches to language processing and demonstrates how they can be used for crucial tasks like machine translation, speech recognition, information extraction, search engines, spelling and grammar correction, and the development of spoken-language dialog agents....

3. “Foundations of Statistical Natural Language Processing”

The book contains all the theory and algorithms that you will ever need for building NLP tools. It broadly covers mathematical and linguistic foundations and also has statistical methods discussed in details. Thus, this book allows the students and researcher to construct their own implementations....

4. “Neural Network Methods in Natural Language Processing”

This book focuses on using neural network models to analyze natural language data. The style of writing in the book invites you to consider the reasons behind things happening and whether you can apply these networks to address specific issues in your own life. Being able to reason about the newest and finest tools is quite helpful, as NLP is still pretty challenging (relative to the field day computer vision has been having)....

5. “Natural Language Understanding”

Natural Language Understanding provides a far better introduction to NLP/AI than Speech and Language Processing (2nd Edition). Even though some jargon is inevitable, NLU uses very little of it and makes it easy to read....

6. “Natural Language Processing with Python”

The book “Natural Language Processing USING Python” will show you how to process natural language. If you’re interested in learning more about natural language processing, it’s best to consult their documentation if you’re already proficient in the field....

7. “Natural Language Processing in Action”

“Natural Language Processing in Action” will help you develop machines that can read and interpret human language. In it, you will use easily accessible Python libraries to extract text’s meaning and respond appropriately. As you go through real-world issues like extracting names and dates, creating text, and responding to open-ended queries, the book broadens the scope of traditional natural language processing (NLP) approaches to encompass neural networks, contemporary deep learning algorithms, and generative techniques. This book requires basic understanding of deep learning and intermediate Python skills....

Additional NLP Books to Consider

Apart from these Top NLP books , You can slo recommend below mentioned books to learn Natural Language Processing (NLP)....

Conclusion

Thus, we have discussed seven books on NLP that you can read straightaway to whet your skills and create some cool applications based on NLP. There are many other books that you may explore, however, we have mentioned the books that are most popular and preferred by the industry experts for their reference. You may choose any of the books by assessing depth of your current knowledge in NLP and what interests you the most....