Python All-in-One, 2nd Ed (For Dummies)

Authors: John Shovic and Alan Simpson
Publisher: For Dummies
Date: April 2021
Pages: 720
ISBN: 978-1119787600
Print: 1119787602
Kindle: B091DGDLK8
Audience: People wanting to learn Python
Rating: 2
Reviewer: Mike James
All-in-one refers to the fact that this is seven books put together - why?

This claims to be seven books in one, but if these are seven are also separately published books I can't find them. It really seems to be an excuse to bundle together chapters on different topics none of which would actually be complete enough to merit being a book in its own right. Of course, if you are looking for just such a mix this might be an advantage.

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Books 1, 2 and 3 are a bit of a cheat in that putting them together gives you what you might expect to find in a standard introduction to Python. Book 1 is getting started, Book 2 is the core Python language and Book 3 is a random collection of applications. Treating these three books as sections in a single book introducing Python would seem fair.

The first problem is that it takes roughly 50 pages to get started  before we reach the first Python program. This is partly because setting things up in any programming language has become more difficult, but it is also because of the use of Anaconda - a Python distribution. Personally I'd prefer a raw installation and to use VS Code or PyCharm as an IDE. I'm sure many readers will give up before they get to the first program.

After this things are very standard and we have a simple introduction to numbers, Lists, Tuples, Dictionaries and finally Class and objects. I can't say I liked the informal presentation, but you might find it friendly. What I did find more of a problem was the lack of insight into what was being introduced. The final part of the introduction, Book 3, deals with using files, working with JSON, using the Internet and packages, libraries and modules.

Overall we have a not particularly special 300-page introduction to Python and splitting it into 3 "books"  is just a gimmick.

 

Book 4 is a lightning introduction to AI - or rather to neural networks with NumPy, Tensorflow and Keras. At just over 100 pages you can't expect much depth and you don't get it. The idea of going from an introduction to Python to implementing a neural network strikes me as being a bad idea, but if you want to follow the instructions you might manage to build a simple neural network - to cover the rest of AI at the same level would take a really big book.

Book 5 is about data science and this is slightly less crazy than following an introduction to Python with AI. It uses NumPy, Pandas and MatPlot to do simple data processing. The last part of the book deals with using Google Cloud to souce data. At just over 30 pages this is just insufficient.

Book 6 is about physical computing - mainly using a Raspberry Pi and, at firs,t the GPIO Zero library. Nearly all of the electronics uses the Grove system of easy-to-use plugable boards. This makes reasonable sense for a beginner. Later we encounter DC motors, servos and steppers. Mostly the programs use off-the- shelf-drivers and the details of what is going on are glossed over. 

Book 7 is more physical computing and is focused on how to build a robot. It also uses some of the ideas from the AI chapters to implement a cat/not cat detector among others.

Conclusion

The main thing to say about this book is that it isn't seven books in one. At best it is four books in one - Python, data processing, AI and physical computing. But the data processing and AI are so slight they wouldn't stand as books in their own right.  The best way to characterise this book is that it covers what you need to know to implement the robot in the final section. Learn Python, AI and some embedded computing and then use it to build a robot is a better description of its contents,

The part of the book that deals with Python is nothing special and there are much better places to start. There is no overall feel of a logical presenation and very little in the way of deeper principles. Certainly basing it on Anaconda and having a huge section on getting started doesnt' do the reader any favors. Getting started with anything these days is tough, but not his tough.

The part of the book on AI is just insufficient and basically you have to take everything on trust. The part on phyiscal computing is shallow - it uses what software is available and never strays into an principles of electronics. The final part looks like a fun project but this is not the way to approach it - you need much more knowledge than you get from just this book.

For our recommendations of introductory books on Python  see Python Books For Beginners in our Programmer's Bookshelf section

 

 

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Artificial Intelligence, Machine Learning, and Deep Learning (Mercury Learning)

Author: Oswald Campesato
Publisher: Mercury Learning
Date: February 2020
Pages: 300
ISBN: 978-1683924678
Print: 1683924673
Kindle: B084P1K9YP
Audience: Developers interested in machine learning
Rating: 4
Reviewer: Mike James

Another AI/ML book - is there room for another one?



Killer ChatGPT Prompts (Wiley)

Author: Guy Hart-Davis
Publisher: Wiley
Pages: 240
ISBN: 978-1394225255
Print: 1394225253
ASIN: B0CF3WFTWM
Audience: Everyone
Rating: 5
Reviewer: Ian Stirk

This book aims to get optimal answers to your questions from ChatGPT, how does it fare? 


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Last Updated ( Wednesday, 27 October 2021 )