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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

By Imran Ahmad
$39.99 $27.98
Book Jun 2020 382 pages 1st Edition
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eBook
$39.99 $27.98
Print
$49.99
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Free Trial
Renews at $15.99p/m

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40 Algorithms Every Programmer Should Know

Section 1: Fundamentals and Core Algorithms

This section introduces us to the core aspects of algorithms. We will explore what an algorithm is and how to design it, and also learn about the data structures used in algorithms. This section also gives a deep idea on sorting and searching algorithms along with the algorithms to solve graphical problems. The chapters included in this section are:

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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.

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

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want

Product Details


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

Table of Contents

19 Chapters
Preface Chevron down icon Chevron up icon
1. Section 1: Fundamentals and Core Algorithms Chevron down icon Chevron up icon
2. Overview of Algorithms Chevron down icon Chevron up icon
3. Data Structures Used in Algorithms Chevron down icon Chevron up icon
4. Sorting and Searching Algorithms Chevron down icon Chevron up icon
5. Designing Algorithms Chevron down icon Chevron up icon
6. Graph Algorithms Chevron down icon Chevron up icon
7. Section 2: Machine Learning Algorithms Chevron down icon Chevron up icon
8. Unsupervised Machine Learning Algorithms Chevron down icon Chevron up icon
9. Traditional Supervised Learning Algorithms Chevron down icon Chevron up icon
10. Neural Network Algorithms Chevron down icon Chevron up icon
11. Algorithms for Natural Language Processing Chevron down icon Chevron up icon
12. Recommendation Engines Chevron down icon Chevron up icon
13. Section 3: Advanced Topics Chevron down icon Chevron up icon
14. Data Algorithms Chevron down icon Chevron up icon
15. Cryptography Chevron down icon Chevron up icon
16. Large-Scale Algorithms Chevron down icon Chevron up icon
17. Practical Considerations Chevron down icon Chevron up icon
18. Other Books You May Enjoy Chevron down icon Chevron up icon

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