The 10 Best Books On Natural Language Processing ( 2018 Update )

The 10 Best Books On Natural Language Processin

The following list offers the top 10 NLP books I recommend you to read. Once you’re done, you will have a VERY solid handle on the field.

What can you expect from reading the NLP books on this list?

The criteria I used to Select these Best Books are: 

 

All-Round Creation, Very Practical, Generative, Affordable, Authorship, Highest Reviewed, Stimulates the mind & imagination, Practical Problems, Career Opportunities, Highest Rated, Can be read over & over, Best Sellers, Newest, Without Bias.

 

 

Without further due, Let’s Get Started!

 

Top 10 Best Books On Natural Language Processing You Should Read Now

 

1.) Speech and Language Processing: An Introduction to Natural Language Processing Computational Linguistics and Speech Recognition

 

Speech-and-Language-Processing-An-Introduction-to-Natural-Language-Processing-Computational-Linguistics-and-Speech-Recognition.

 

An explosion of Web-based language techniques, merging of distinct fields, availability of phone-based dialogue systems and much more make this an exciting time in speech and language processing.

The first of its kind to thoroughly cover language technology – at all levels and with all modern technologies – this text takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations.

 

Available: Buy Now

 

2.) Natural Language Processing with Python

 

Natural-Language-Processing-with-Python

 

This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation.

With it, you will learn how to write Python programs that work with large collections of unstructured text. You will access richly annotated datasets using a comprehensive range of linguistic data structures and you will understand the main algorithms for analyzing the content and structure of written communication.

 

Available: Buy Now

 

3.) Foundations of Statistical Natural Language Processing

 

Foundations-of-Statistical-Natural-Language-Processing

Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools.

It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.

 

Available: Buy Now

 

3.) Statistical Methods for Speech Recognition

 

Statistical-Methods-for-Speech-Recognition

 

This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions.

The author’s goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques.

 

Available: Buy Now

 

4.) Graph-based Natural Language Processing and Information Retrieval

 

Graph-based-Natural-Language-Processing-and-Information-Retrieval

 

Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these areas have been perceived as distinct, with different algorithms, different applications and different potential end-users.

However, recent research has shown that these disciplines are intimately connected, with a large variety of natural language processing and information retrieval applications finding efficient solutions within graph-theoretical frameworks.

 

Available: Buy Now

 

5.) Natural Language Processing for Online Applications: Text Retrieval, Extraction and Categorization

 

Natural-Language-Processing-for-Online-Applications-Text-Retrieval-Extraction-and-Categorization

 

This text covers the technologies of document retrieval, information extraction, and text categorization in a way which highlights commonalities in terms of both general principles and practical concerns.

It assumes some mathematical background on the part of the reader, but the chapters typically begin with a non-mathematical account of the key issues.

 

Available: Buy Now

 

6.) Python Text Processing with Nltk 2.0 Cookbook

 

Python-Text-Processing-with-Nltk-2.0-Cookbook

 

The learn-by-doing approach of this book will enable you to dive right into the heart of text processing from the very first page. Each recipe is carefully designed to fulfill your appetite for Natural Language Processing. Packed with numerous illustrative examples and code samples.

It will make the task of using the NLTK for Natural Language Processing easy and straightforward. This book is for Python programmers who want to quickly get to grips with using the NLTK for Natural Language Processing. 

 

Available: Buy Now

 

7.) Building Natural Language Generation Systems

 

Building-Natural-Language-Generation-Systems

 

This book explains how to build Natural Language Generation (NLG) systems – computer software systems which use techniques from artificial intelligence and computational linguistics to automatically generate understandable texts in English or other human languages, either in isolation or as part of multimedia documents, Web pages, and speech output systems. 

 

Available: Buy Now

 

8.) The Oxford Handbook of Computational Linguistics

 

The-Oxford-Handbook-of-Computational-Linguistic

 

Thirty-eight chapters, comissioned from experts all over the world, describe major concepts, methods, and applications in computational linguistics. Part I, Linguistic Fundamentals, provides an overview of the field suitable for senior undergraduates and non-specialists from other fields of linguistics and related disciplines.

Part II describes current tasks, techniques, and tools in Natural Language Processing and aims to meet the needs of post-doctoral workers.

 

Available: Buy Now

 

10.) Computational Nonlinear Morphology: With Emphasis on Semitic Languages

 

Computational-Nonlinear-Morphology-With-Emphasis-on-Semitic-Languages

 

The book outlines a generalized regular rewrite rule system that employs multi-tape finite-state automata to cater for root-and-pattern morphology, infixation, circumfixation and other complex operations such as the broken plural derivation problem found in Arabic and Ethiopic.

 

Available: Buy Now

 

FINAL WORDS

 

Start Understanding these books One by One. Perhaps, a $8-10 book can change your Career for eternity.

Books changed my life in recent years. I was forced to peruse books in my formal education and avoided from perusing books in my corporate activity.

 

About Manjunath 97 Articles
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