Book Image

40 Algorithms Every Programmer Should Know

By : Imran Ahmad
5 (2)
Book Image

40 Algorithms Every Programmer Should Know

5 (2)
By: Imran Ahmad

Overview of this book

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.
Table of Contents (19 chapters)
1
Section 1: Fundamentals and Core Algorithms
7
Section 2: Machine Learning Algorithms
13
Section 3: Advanced Topics

Understanding linear programming

The basic algorithm behind linear programming was developed by George Dantzig at the University of California at Berkeley in the early 1940s. Dantzig used this concept to experiment with logistical supply-and-capacity planning for troops while working for the US Air Force. At the end of the Second World War, Dantzig started working for the Pentagon and matured his algorithm into a technique that he named linear programming. It was used for military combat planning.

Today, it is used to solve important real-world problems that relate to minimizing or maximizing a variable based on certain constraints. Some examples of these problems are as follows:

  • Minimizing the time to repair a car at a mechanic shop based on the resources

  • Allocating available distributed resources in a distributed computing environment to minimize response times

  • Maximizing the...