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40 Algorithms Every Programmer Should Know
40 Algorithms Every Programmer Should Know

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

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Profile Icon Imran Ahmad
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$12.99 per month
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.8 (32 Ratings)
Paperback Jun 2020 382 pages 1st Edition
eBook
$39.99
Paperback
$49.99
Subscription
Free Trial
Renews at $12.99p/m
Arrow left icon
Profile Icon Imran Ahmad
Arrow right icon
$12.99 per month
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.8 (32 Ratings)
Paperback Jun 2020 382 pages 1st Edition
eBook
$39.99
Paperback
$49.99
Subscription
Free Trial
Renews at $12.99p/m
eBook
$39.99
Paperback
$49.99
Subscription
Free Trial
Renews at $12.99p/m

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Key benefits

  • Learn the techniques you need to know to design algorithms for solving complex problems
  • Become familiar with neural networks and deep learning techniques
  • Explore different types of algorithms and choose the right data structures for their optimal implementation

Description

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.

Who is this book for?

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.

What you will learn

  • Explore existing data structures and algorithms found in Python libraries
  • Implement graph algorithms for fraud detection using network analysis
  • Work with machine learning algorithms to cluster similar tweets and process Twitter data in real time
  • Predict the weather using supervised learning algorithms
  • Use neural networks for object detection
  • Create a recommendation engine that suggests relevant movies to subscribers
  • Implement foolproof security using symmetric and asymmetric encryption on Google Cloud Platform (GCP)

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 12, 2020
Length: 382 pages
Edition : 1st
Language : English
ISBN-13 : 9781789801217
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Product Details

Publication date : Jun 12, 2020
Length: 382 pages
Edition : 1st
Language : English
ISBN-13 : 9781789801217
Category :
Languages :

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Customer reviews

Top Reviews
Rating distribution
Full star icon Full star icon Full star icon Half star icon Empty star icon 3.8
(32 Ratings)
5 star 53.1%
4 star 15.6%
3 star 6.3%
2 star 9.4%
1 star 15.6%
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Ivan and Zorro Mar 22, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Easy enough for beginning programmers to use and digest. This book is well and clearly written. There is some traditional algorithm coverage, but the main focus is on writing machine learning algorithms. Starts at the beginning and assumes no knowledge of Python, although familiarity with a programming language will help it doesn’t have to be Python. I guess if you are new to Python though you will quickly fall in love. While there is something to be said of language agnostic algorithm, it is nice to have discussion and implantation in the same book and in a modern language.
Amazon Verified review Amazon
Math_Ninja Jun 23, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I am using this book to get an overview of the algorithms that I am working on. It covers a wide variety of the algorithms. Presenting actual examples helps. I have not tried downloading and running code as yet.
Amazon Verified review Amazon
Donald A. Newell Jr. Apr 21, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Good refresher for programmers who do not remember everything from their computer science class (like myself).
Amazon Verified review Amazon
Chris Mawata Dec 18, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This is a book someone starting out should read cover to cover and someone already in the field should keep on the bookshelf for those days when you remember there is a standard algorithm that does something you want but you can't quite remember how it is implemented.
Amazon Verified review Amazon
RT Jul 30, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Who the book is aimed at: if you self-identify as a data scientist, serious algorithms specialist, or even the quant type, then you won’t be disappointed! If you’re just starting in the field, the author has done the hard work of selecting some of the commonly used techniques & algorithms in the field today.The content’s breadth and depth is masterfully selected, it won’t disappoint!Style & Language: easy to read plain english; the book does have a strong Python flavour (v3.7+), but even R-focused practitioners will likely find some of the content rewarding.Examples: the diagrams/figures convey the basic ideas very well, and the author has also setup a live git repo, and it seems he does plan to keep it updated.PS. Having just started this book review, it’s is a work-in-progress, I’ll update as I go through more chapters.
Amazon Verified review Amazon
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