40 Algorithms Every Programmer Should Know: Hone your problem-solving skills by learning different algorithms and their implementation in Python

by Imran Ahmad

Learn algorithms for solving classic computer science problems with this concise guide covering everything from fundamental algorithms, such as sorting and searching, to modern algorithms used in machine learning and cryptography Algorithms have always played an important role in both the science and practice of computing. Beyond traditional computing, the ability to use algorithms to solve real-world problems is an important skill that any developer or programmer must have. This book will help you not only to develop the skills to select and use an algorithm to solve real-world problems but also to understand how it works. You’ll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, such as searching and sorting, with the help of practical examples. As you advance to a more complex set of algorithms, you'll learn about linear programming, page ranking, and graphs, and even work with machine learning algorithms, understanding the math and logic behind them. Further on, case studies such as weather prediction, tweet clustering, and movie recommendation engines will show you how to apply these algorithms optimally. Finally, you’ll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks. By the end of this book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms. This book is for programmers or developers who want to understand the use of algorithms for problem-solving and writing efficient code. Whether you are a beginner looking to learn the most commonly used algorithms in a clear and concise way or an experienced programmer looking to explore cutting-edge algorithms in data science, machine learning, and cryptography, you'll find this book useful. Although Python programming experience is a must, knowledge of data science will be helpful but not necessary.

Genres: Programming, Algorithms, Computer Science, Technology, Software

374 pages, Paperback

Published June 12, 2020

About the author

Imran Ahmad is affiliated with the Food Engineering and Bioprocess Technology program at the Asian Institute of Technology, Thailand.

Reviews

[Daval Davis · Rating 1 out of 5]

Rubbish. Skips around topics, without any actual depth. And it has all of the editorial expertise that i've come to expect from Packt books, which is to say, no editing at all. Page 39 shows a lambda that squares values, and then describes it as "Multiplication by two". Page 64 illustrates insertion sort with a diagram of shell sort.

At best, this book would serve as a source for topics you might want to look up in other, better books.

[Marek Sirkovský · Rating 1 out of 5]

The book is not good. There are many difficult to grasp concepts without proper explanation. Just superficial algorithm descriptions. The book's name should be a brief catalog of algorithms.

[Vishwanath · Rating 2 out of 5]

The table of contents was comprehensive and a bit ambitious to be fair. Great outline for anyone wanting to learn a host of subjects from Supervised/Unsupervised ML, Cryptography, Basic data processing concepts and storage algorithms. The list of algorithms was well summarized and small examples that serve as good reference material for a quick refresher. Brevity was an advantage and disadvantage here as the concise chapters were engaging and to the point. However, the vastness of the subject matter left little space for the author to dive in deep into any area. Some chapters felt like a mashup of material across different topics. Also, the organization of the book ( e-book on the safari website in my case) was poor - the algorithms don't seem to be numbered per a sequence and the table of contents were not either - not sure if the publisher is still making edits though the release date indicates June 2020. The code consists of simple implementations in scikit-learn which is useful for the ML algorithms as a quick refresher.

[Jascha · Rating 2 out of 5]

A very disappointing book. The choice of the presented algorithms is limited. Each is described very shortly.

[Nate F · Rating 1 out of 5]

A messy unsourced blob of keywords. Mostly about machine learning, not really about algorithms in general.

This has no works cited, was clearly not peer reviewed, and the editor didn’t catch several formatting issues (such as incorrect figures). The author himself doesn’t seem to be a credible source. Experience in teaching beginner python courses, even if it’s google paying him, does not qualify the author as an authoritative source on machine learning.

The learning curve was very jagged. At times it was so slow it feels like a beginner book, and other times it reads like the GNU Haskell Compiler Manual in just how fast it expects the reader to pick things up.

Often it feels out-of order, and I’m not sure where the number 40 came from.

After chapter five or so, none of the python libraries (which are extremely use-case specific) are explained. The code using the library is merely shown, even though it would be very on-topic to explain the “why” of the code they show instead of only a cursory explanation of what this code might be used for.

If a second edition of this book were to be released, I might read it, but in its current state I cannot recommend this book to educators, hobbyists, or professionals wanting to expand horizons.

[Marc Buraczynski · Rating 2 out of 5]

I thought the organization of the book was good but the in-depth examples that are really needed were not there. I like the beginner's aspect but that's about as far as I would see this being useful. If you are new to Data Science or Machine Learning, I can recommend the book as a feasible primer. The examples were good but overall, I'd recommend more of a code repository approach where the author would demonstrate with the limited examples as shown then forward to the public repository for end-to-end code.

[Brandon Denning · Rating 4 out of 5]

Decent overview but lacks depth

Covers a lot of different algorithm types and their uses but many are glossed over or oversimplified. I can't really fault the author though as the book would need to be 10x as long to cover each in depth.

The expected categories are covered though (sorting, graph traversal, etc). When you get to areas like hashing though, they cover 2 common ones (MD5 and SHA-512) and explain how, in general - as you would give to a non-programmer, hashing works and how to run in Python using a library.

[Johnny · Rating 2 out of 5]

It starts very academically but for the first chapter that style worked. It showed the importance of algorithms and how many mistakes in software development could be stopped at an early point. Unfortunately, the book keeps going on at a too academic level, what may be useful for a course at a university. For everyone else, the style gets boring too fast, and I missed an explanation on why it selected those 40 algorithms and not different ones. There are a few interesting problems discussed in the book, but again, split over so many parts that it is annoying to get the full picture.

[esplovago · Rating 1 out of 5]

Un insieme di contenuti senza alcun filo logico, per giunta spiegati male (a volte in maniera superficiale, altre in maniera iper-tecnica).

Inoltre la traduzione italiana contiene vari errori di battitura e anche alcuni termini tradotti in maniera non propriamente corretta (questo è strano per Apogeo, che solitamente fornisce ottime traduzioni).

[Evan Pacini · Rating 2 out of 5]

A great source of inspiration, but not a source of information. The topics in the book are all quickly ran over without any kind of depth, making it difficult to learn anything from the book. However, the topics are quite interesting, but not enough for me to recommend the book.

[Mario Vukašinović · Rating 2 out of 5]

Barely usable. Misleading title.

[Hongjian Wang · Rating 1 out of 5]

not worth reading
if you know the concept already, then you finish the book in 40 minutes.
if you don't know the concept previously, i doubt you will learn them in this book