|Top Computing Theory Book Choices|
|Written by Kay Ewbank|
|Monday, 23 March 2020|
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Author: Tony Hey and Gyuri Pápay
Subtitled "A journey through a revolution", this book is targeted at students with the aim of stimulating their interest in “the wide range of career opportunities in computer science”, but Sue Gett thinks it would appeal to a wider audience and has given it five stars. She says the book is mostly highly accessible and when it is more difficult you are advised to skim, read or skip. A case in point is Chapter 6: Mr Turing's amazing machines, acknowledged in the preface as the most difficult in the book as it explores idea that are the theoretical basis for much of computer science. Other chapters cover algorithms, programming languages, hardware, the Internet, and artificial intelligence, all taking a route from the beginnings through to the present day.
Overall, Sue says that while it is intended to be intelligible to both high school and first-year university students, it has a lot to offer the general reader and even those already part of the computing universe as a coherent, well-written account of its past, present and future. Highly recommended.
Author: John V Guttag
This is the text book for the Introduction to Computer Science and Programming Using Python MOOC on edX, which is co-taught by its author John Guttag. As such, it is not a dummy's book and it isn't exclusively focused on teaching you to code in Python. This is a more general book on the ideas and practice of programming and algorithm construction - it also has a slightly academic feel to it, even though the style is casual and there are lots of encouraging words. It impressed Mike James enough for him to award it the maximum five stars.
The range of topics explored leans towards the statistics side of the science and it would make a good book for any student studying almost any STEM subject. Expect to learn as much about stats as computing as you progress.
Since Mike reviewed the book, there's been a new edition updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and with additions including expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics. As long as you are the right reader, this is the right book and comes Highly Recommended.
Author: Alan P. Parkes
This is a book about the theory of formal languages, grammar and abstract machines such as the Turing machine, and Mike James said it’s the sort of material covered in any good computer science degree, and gave the book four stars, saying:
"What is special about this particular text book is that it attempts to introduce the very mathematical ideas of formal grammars and symbolic manipulation in a way that is easy to understand even if you don’t know much modern maths."
Mike said that by the end of the book the reader should be able to appreciate the big questions such as P=NP? and will be either ready to move on to something more advanced or will be better educated in the very basics of computational theory. He concluded that this is a good book but it isn’t suitable as a general non-technical introduction.
|Last Updated ( Tuesday, 24 March 2020 )|