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

Learn algorithms for solving classic computer scienceproblems with this concise guide covering everything fromfundamental algorithms, such as sorting and searching, to modernalgorithms used in machine learning and cryptographyKey FeaturesLearn the techniques you need to know to design algorithms forsolving complex problemsBecome familiar with neural networks and deep learningtechniquesExplore different types of algorithms and choose the right datastructures for their optimal implementationBook DescriptionAlgorithms have always played an important role in both the scienceand practice of computing. Beyond traditional computing, theability to use algorithms to solve real-world problems is animportant skill that any developer or programmer must have. Thisbook will help you not only to develop the skills to select and usean algorithm to solve real-world problems but also to understandhow it works.You'll start with an introduction to algorithms and discovervarious algorithm design techniques, before exploring how toimplement different types of algorithms, such as searching andsorting, with the help of practical examples. As you advance to amore complex set of algorithms, you'll learn about linearprogramming, page ranking, and graphs, and even work with machinelearning algorithms, understanding the math and logic behind them.Further on, case studies such as weather prediction, tweetclustering, and movie recommendation engines will show you how toapply these algorithms optimally. Finally, you'll become wellversed in techniques that enable parallel processing, giving youthe ability to use these algorithms for compute-intensivetasks.By the end of this book, you'll have become adept at solvingreal-world computational problems by using a wide range ofalgorithms.What you will learnExplore existing data structures and algorithms found in PythonlibrariesImplement graph algorithms for fraud detection using networkanalysisWork with machine learning algorithms to cluster similar tweetsand process Twitter data in real timePredict the weather using supervised learning algorithmsUse neural networks for object detectionCreate a recommendation engine that suggests relevant movies tosubscribersImplement foolproof security using symmetric and asymmetricencryption on Google Cloud Platform (GCP)Who this book is forThis book is for the serious programmer! Whether you are anexperienced programmer looking to gain a deeper understanding ofthe math behind the algorithms or have limited programming or datascience knowledge and want to learn more about how you can takeadvantage of these battle-tested algorithms to improve the way youdesign and write code, you'll find this book useful. Experiencewith Python programming is a must, although knowledge of datascience is helpful but not necessary.Table of ContentsOverview of AlgorithmsData Structures used in AlgorithmsSorting and Searching AlgorithmsDesigning AlgorithmsGraph AlgorithmsUnsupervised Machine Learning AlgorithmsTraditional Supervised Learning AlgorithmsNeural Network AlgorithmsAlgorithms for Natural Language ProcessingRecommendation EnginesData AlgorithmsCryptographyLarge Scale AlgorithmsPractical Considerations