5 Free Natural Language Processing Books to Read in 2023

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Before the hype around Large Linguistic Models (LLMs) began, NLP was built but progressing. Now it has become a revolution since LLM like ChatGPT came out. LLMs have been shown to understand and produce human-like text. Models such as ChatGPT, Google Bard, and others have been trained on large volumes of textual data using deep neural network architectures.

But how exactly do these models understand people and how do they produce human-like responses? NLP. A subfield of artificial intelligence that helps models process, understand, and interpret human language. They are typically trained in tasks such as predicting next words, which allow them to form contextual dependencies and then be able to generate relevant outputs. The NLP field has advanced applications such as chatbots, text summarization and more.

There are some ethical concerns about LLMs and their biases in generating text, which has led to further research into NLP and its use in LLM applications. Although these problems and challenges are currently being addressed, LLM models such as ChatGPT have had a world impact – it seems they are here to stay and an understanding of NLP will be essential.

If you want to know more about LLMs, you should check out NLP. In this article, I will review 5 free books you should read in 2023 to better understand NLP.

Authors: Dan Yurafsky and James H. Martin

Name: Speech and language processing

Written by two university professors, this speech and language processing book offers a perfect introduction to the world of NLP. It is divided into 3 parts: Fundamental Algorithms for NLP, NLP Applications and Linguistic Structure Annotation. The first part is essential for beginners to better understand what NLP is, its basics with examples that break it down. You will come across various topics like semantics, syntax and more.

If you are new to the field of NLP or want to move into the field, I truly believe this book will be very helpful for individual study. As the professors wrote, practical examples help the reader understand the concepts better than a purely theoretical book.

Authors: Christopher D. Manning and Hinrich Schütze

Name: Fundamentals of statistical natural language processing

If you are a data professional, or in the world of artificial intelligence – you will know how important statistics are in this field. Some believe that you don’t need to have a high understanding of the sector, however I believe it is important as it will make your data career journey much smoother.

When you have a good foundation of the NLP field, you might think that the next step is to learn about algorithms. Before that, you’ll want to learn more about the mathematical foundations of the language. Not only does this book begin with the basics of NLP, it explores mathematical aspects such as probability spaces, Bayes’ theorem, variance, and more.

Author: Christopher M. Bishop

Name: Pattern Recognition and Machine Learning

The best way to understand how models work is to understand how the model works, its train of thought, pattern recognition, and why it produces what it does. Pattern recognition is the process of distinguishing data based on set criteria performed by special algorithms. It enables learning and enables improvement, which makes machine learning algorithms and their performance very important.

Each chapter has an exercise at the end, chosen to better explain each concept to the reader. The author has kept the mathematical content to a minimum to help the reader understand better, although he notes that a good understanding of calculus, linear algebra, and probability theory would be helpful to understand pattern recognition and machine learning techniques.

Author: Yoav Goldberg

Name: Neural Network Methods in NLP

When studying the growth of NLP, we can say that neural networks played a big role. Neural networks provide NLP models with a better understanding of human language, allowing them to predict words and categorize different topics that were not previewed to them during learning.

This book does not immediately explore the implications of neural networks. It begins by exploring basics such as linear models, perceptrons, feedforward, neural network training, and more. The author uses a mathematical approach to explain these fundamental elements along with practical examples.

Authors: Soumya Vajla, Bodhisattva Majumderi, Anuj Gupta and Harshit Surana

Name: Practical natural language processing

So you understand speech and language, you’ve covered statistical NLP, then look at pattern recognition and neural networks in NLP. The last thing you need to learn is the practical application of NLP.

This book discusses how NLP is used in the real world, the pipeline of NLP models, and more on textual data and use cases such as Chatbots such as ChatGPT. In this book, you will learn how NLP can be used in various sectors such as retail, healthcare, finance, and more. With different sectors, you’ll be able to gauge how the NLP pipeline is performing for each and figure out how to use it for yourself.

The aim and purpose of this article was to provide you with 5 free books that I believe are essential and useful for your NLP career or study. Although I’ve done this in a structured format, I hope that each book takes the other to the next level in your learning.

If there are other free NLP books that you think others would benefit from, please drop them in the comments!

There is a niche is a data scientist, freelance technical writer and community manager at KDnuggets. He is particularly interested in data science career advice or tutorials and theory-based knowledge about data science. He also wants to explore different ways in which artificial intelligence is/can benefit from human longevity. An eager learner looking to expand his technical knowledge and writing skills while helping others.