AI Books To Inspire You
Written by Kay Ewbank   
Monday, 30 November 2020
Article Index
AI Books To Inspire You
Natural Language Processing and Deep Learning Titles


Handbook of Natural Language Processing (2e)

Author: Nitin Indurkhya & Fred J. Damerau (Editors)
Publisher: Chapman and Hall/CRC
Pages: 804
ISBN: 978-1420085921

In looking for a Best Book selection in the Artificial Intelligence catagory, Mike James selected a highly readable collection of papers on Natural Language Processing. Awarding it 5 stars, Mike said that while you might guess that it is going to be another boring collection of difficult to read papers - only you would be wrong! If you need a readable introduction to this important subject - this is it.


This is a good way to get into NLP. You will probably need additional, more specialized, texts to guide your next steps but this does provide a basic course on the subject suitable both for academic and practical development.

Highly recommended.

Natural Language Processing with Python

Author: Steven Bird, Ewan Klein & Edward Loper
Publisher: O'Reilly
Pages: 502
ISBN: 978-0596516499

Mike James says this book is likely to get you enthusiastic about language processing, and gave it 4.5 stars while remaining skeptical about whether this is a good thing. The Python NLTK Natural Language Toolkit is used to demonstrate practical natural language processing rather than theory., and the book starts from simple things - almost just text processing.


Mike's conclusion is that if you are thinking about adding natural language processing to any sort of application this is a must read book. It is also great fun and if have any interest in AI you will enjoy reading it.  His caveat is that if you want to be reminded of how difficult the natural language problem is just read the Afterword. The sentences listed there are enough to make you realise that language is a wonderful invention. 

Advanced Deep Learning with TensorFlow 2 and Keras, 2nd Ed

Author: Rowel Atienza
Publisher: Packt Publishing
Pages: 512
ISBN: 978-1838821654

This is a book for developers wanting to master neural networks,and while it isn't an advanced theoretical text, it does offer a wide range of advanced examples, according to Mike James, who gave it a maximum five star rating. 

He says that the examples go well beyond the basic introductions to any of the topics that you will find in most other books, and is very strong on GANs and if this is an area that interests you then so much the better.

Foundations of Deep Reinforcement Learning  

Authors: Laura Graesser and Wah Loon Keng
Publisher: Addison-Wesley
Pages: 416
ISBN: 978-0135172384

This book is excellent and Mike James, awarding it five stars, says that if you have any interest in reinforcement learning just buy it, read it and learn. It is a guide to the theory and the practice, and while it isn't an easy book to read and it will take you some time to actually read very much of it, this is because the subject matter is difficult and the book does its best to explain and motivate it.


Even so, as already stated, you are going to have to be happy reading quite complicated equations and understanding them. The only way that this could have been avoided is by not telling you how things work and this is not the intention of this book. Mike's conclusion is that this is an excellent book, and if you are in, or want to be in, the field you should read it.


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SQL Server 2022 Query Performance Tuning (Apress)

Author: Grant Fritchey
Publisher: Apress
Pages: 745
Audience: DBAs & SQL Devs
Rating: 4.7
Reviewer: Ian Stirk 

A popular performance tuning book gets updated for SQL Server 2022, how does it fare?

SQL Query Design Patterns and Best Practices

Author: Steve Hughes et al
Publisher: Packt Publishing
Pages: 270
ISBN: 978-1837633289
Print: 1837633282
Kindle: B0BWRD7HQ7
Audience: Query writers
Rating: 2.5
Reviewer: Ian Stirk

This book aims to improve your SQL queries using design patterns, how does it fare? 

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<ASIN: 0135172381>


Last Updated ( Tuesday, 01 December 2020 )