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


40 Algorithms Every Programmer Should Know: Hone your problem-solving skills by: learning different algorithms and their implementation in Python
by: Imran Ahmad
Print Length 页数: 382 pages
Publisher finelybook 出版社: Packt Publishing (12 Jun. 2020)
Language 语言: English
ISBN-10: 1789801214
ISBN-13: 9781789801217


Book Description
By finelybook

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
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)

Table of Contents
Preface
Section 1: Fundamentals and Core Algorithms
Chapter 1: Overview of Algorithms
Chapter 2: Data Structures Used in Algorithms
Chapter 3: Sorting and Searching Algorithms
Chapter 4: Designing Algorithms
Chapter 5: Graph Algorithms
Section 2: Machine Learning Algorithms
Chapter 6: Unsupervised Machine Learning Algorithms
Chapter 7: Traditional Supervised Learning Algorithms
Chapter 8: Neural Network Algorithms
Chapter 9: Algorithms for Natural Language Processing
Chapter 10: Recommendation Engines
Section 3: Advanced Topics
Chapter 11: Data Algorithms
Chapter 12: Cryptography
Chapter 13: Large-Scale Algorithms
Chapter 14: Practical Considerations
Other Books You May Enjoy
Index

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