Natural Language Processing Books – 5 Best Books You Should Read in 2021

We have come up with the best natural language processing books, which will definitely help you get more understanding of the field.
Natural Language Processing Books

Natural Language Processing (NLP) is one of the fastest evolving technology. In essence, NLP is a subfield of artificial intelligence, mainly concerned with training machines (computers) to read, analyze, process, and drive meaning from human language. Natural Language Processing enables developers to organize and structure knowledge from any digital content, including videos, audio, and text. More recently, NLP algorithms have become robust enough to content and perform sentiment analysis, speech recognition, topic segmentation, and entity recognition.

What sets NLP apart from a common word processor is its ability to understand the hierarchical structure of languages and not look at the text as a mere sequence of symbols. NLP algorithms can understand and differentiate words, phrases, sentences and ultimately make sense out of those sentences. The ability of NLP to perform sentiment analysis, topic segmentation, and entity recognition have resulted in the use of technology in various roles like speech-to-text conversion, translations, and correcting grammar.

Moreover, the ability of NLP to analyze text and understand human language has led to greater collaboration between humans and machines. Some of the potential applications of NLP include; topic summarization, sentiment analysis, parts-of-speech tagging, stemming, entity recognition, best speech-to-text apps, machine translation, automated question answering, and text mining.

If you are looking to start a career in the in-demand NLP field, continue to read as below, we have come up with the top five natural language processing books, which will definitely help you get more command and understanding of the field and start your career as an NLP developer.

5 Best Natural Language Processing Books You Should Read

With the widespread application of the technology across multiple industries, NLP has become a hot industry for young developers looking to gain more insights into the field. And with endless learning resources available online, it’s only understandable that books are often overlooked as a credible learning resource. However, in reality, books usually deliver the most practical and detailed information about the topic, which isn’t covered in blogs, tutorials, and online courses available over the internet.

Below are the 5 best NLP books for your reading, which will definitely help you understand the technology. These books cover almost every part of the NLP technology and are a worthy investment if you want to become a learned and experienced NLP developer. So, let’s see what we have got in our baggage below;

1. Natural Language Processing with Python

Natural Language Processing with Python is a great NLP introductory book written by Steven Bird, Ewan Klein & Edward Loper. The book takes a practical learning approach towards NLP from the point of view of the Python ecosystem. The book heavily relies on the NLTK library, which is definitely a great software to learn NLP.

The practical approach taken in the book ensures that the reader is able to grab the core concepts of the technology aptly. So, if you are looking to get introduced to the various functions and concepts of NLP, this book is an excellent Launchpad to get started with implementing NLP solutions with Python.

2. Natural Language Processing with PyTorch

Natural Language Processing with PyTorch is yet another fantastic reading resource for youngsters looking to get started with the NLP field. The book is written by Dilip Rao & Brian McMahan and is centered around introducing the traditional NLP techniques for developers using neural networks. Just like the book mentioned above, the Natural Language Processing with PyTorch takes the practical approach to the subject and dives straight into the application of PyTorch to implement neural network NLP methods.

This is an excellent resource for developers looking to transit from traditional NLP techniques (non-neural network bases techniques) to more automated NLP techniques.

3. Neural Network Methods for Natural Language Processing

Written by Yoav Goldberg, the Neural Network Methods for Natural Language Processing book takes a deeper dive into explaining the concepts of neural network methods for NLP. Unlike the “Natural Language Processing with PyTorch” that is more about implementing neural network codes for NLP implementation, this book takes a more detailed approach to defining the core concepts without burdening the reader with implementing concepts through codes.

The book is undoubtedly a great resource to understand the core concepts of neural network methods for NLP and help readers get knowledgeable about various neural network-based approaches to NLP work.

4. Linguistic Fundamentals for Natural Language Processing

Getting familiar with linguistic fundamentals is essential before you start working with NLP. The Linguistic Fundamentals for Natural Language Processing by Emily M. Bender is about bridging the gap between computational linguistics for NLP implementation. This book is ideally organized in 100 separate “essentials” to help readers understand better the morphology, syntax, and other essentials of the linguistic.

It’s an ideal book for readers who don’t have much understanding of computational linguistics. While it surely will be a painstaking read, it’s definitely worth your time, as you will be able to develop your core linguistic skills that will go a long way into your NLP career.

5. Natural Language Processing in Action

With Natural Language Processing in Action by Hobson Lane, Hannes Hapke & Cole Howard, we return to the practical application of NLP. The book discusses both the traditional (non-neural network-based) and modern (neural network-based) approaches to the NLP. It introduces various practical coding solutions using multiple available tools like Keras, TensorFlow, and others to help readers develop practical NLP implementation skills.

Also, since it is the most recently released book (out of the books listed in this blog), it contains the most up-to-date content used in the market today. However, this doesn’t mean that the previous books are not worth reading since those books will definitely help you develop the core understanding of the technology you need to become a successful NLP developer.

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