40 Algorithms Every Programmer Should Know

As a programmer, understanding algorithms is crucial for solving complex problems efficiently and creating optimized solutions. Algorithms are step-by-step procedures that allow computers to perform specific tasks.

In this article, we will explore 40 essential algorithms every programmer should know, providing a comprehensive overview of the most commonly used ones across various programming languages.

1. Linear Search Algorithm

Linear Search Algorithm is a simple search algorithm that sequentially checks each element in a list until a match is found or the end of the list is reached.

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

by Imran Ahmad (1st Edition, Kindle Edition)

4.3 out of 5

Language	:	English
File size	:	27745 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	384 pages

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2. Binary Search Algorithm

Binary Search Algorithm is an efficient search algorithm that divides a sorted list into halves, eliminating the half that does not contain the target value until the target value is found or the list is empty.

Mastering these 40 algorithms will greatly enhance your problem-solving skills and make you a more efficient programmer. Remember, algorithms are essential tools that can help you tackle complex tasks and optimize your code to achieve better performance.

Start learning and implementing these algorithms in your coding practice to become a well-rounded programmer who can confidently solve any programming challenge that comes your way.

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

by Imran Ahmad (1st Edition, Kindle Edition)

4.3 out of 5

Language	:	English
File size	:	27745 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	384 pages

FREE

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

Key Features

• 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

Book 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 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)

Who this book is 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.

Table of Contents

1. Overview of Algorithms
2. Data Structures used in Algorithms
3. Sorting and Searching Algorithms
4. Designing Algorithms
5. Graph Algorithms
6. Unsupervised Machine Learning Algorithms
7. Traditional Supervised Learning Algorithms
8. Neural Network Algorithms
9. Algorithms for Natural Language Processing
10. Recommendation Engines
11. Data Algorithms
12. Cryptography
13. Large Scale Algorithms
14. Practical Considerations