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دانلود کتاب algorithms for dummies
English Title : Algorithms For Dummies (For Dummies (Computer/Tech))
عنوان فارسی : الگوریتم های for Dummies

Description

Discover how algorithms shape and impact our digital world

All data, big or small, starts with algorithms. Algorithms are mathematical equations that determine what we see—based on our likes, dislikes, queries, views, interests, relationships, and more—online. They are, in a sense, the electronic gatekeepers to our digital, as well as our physical, world. This book demystifies the subject of algorithms so you can understand how important they are business and scientific decision making.

Algorithms for Dummies is a clear and concise primer for everyday people who are interested in algorithms and how they impact our digital lives. Based on the fact that we already live in a world where algorithms are behind most of the technology we use, this book offers eye-opening information on the pervasiveness and importance of this mathematical science—how it plays out in our everyday digestion of news and entertainment, as well as in its influence on our social interactions and consumerism. Readers even learn how to program an algorithm using Python!

  • Become well-versed in the major areas comprising algorithms
  • Examine the incredible history behind algorithms
  • Get familiar with real-world applications of problem-solving procedures
  • Experience hands-on development of an algorithm from start to finish with Python

If you have a nagging curiosity about why an ad for that hammock you checked out on Amazon is appearing on your Facebook page, you'll find Algorithm for Dummies to be an enlightening introduction to this integral realm of math, science, and business.

Table of contents

Part 1 Getting Started with Algorithms
Chapter 1 Introducing Algorithms
Chapter 2 Considering Algorithm Design
Chapter 3 Working with Google Colab
Chapter 4 Performing Essential Data Manipulations Using Python
Chapter 5 Developing a Matrix Computation Class
Part 2 Understanding the Need to Sort and Search
Chapter 6 Structuring Data
Chapter 7 Arranging and Searching Data
Part 3 Exploring the World of Graphs
Chapter 8 Understanding Graph Basics
Chapter 9 Reconnecting the Dots
Chapter 10 Discovering Graph Secrets
Chapter 11 Getting the Right Web page
Part 4 Wrangling Big Data
Chapter 12 Managing Big Data
Chapter 13 Parallelizing Operations
Chapter 14 Compressing and Concealing Data
Part 5 Challenging Difficult Problems
Chapter 15 Working with Greedy Algorithms
Chapter 16 Relying on Dynamic Programming
Chapter 17 Using Randomized Algorithms
Chapter 18 Performing Local Search
Chapter 19 Employing Linear Programming
Chapter 20 Considering Heuristics
Part 6 The Part of Tens
Chapter 21 Ten Algorithms That Are Changing the World
Chapter 22 Ten Algorithmic Problems Yet to Solve
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John Mueller

John Mueller

John Mueller is a freelance author and technical editor. He has writing in his blood, having produced 117 books and over 600 articles to date. He has also written his second children's book recently, Tail of the Wuggly Bump. His technical topics range from networking to artificial intelligence and from database management to heads down programming. His most recent book is "Machine Learning for Dummies, 2nd Edition." His technical editing skills have helped over 70 authors refine the content of their manuscripts. You can reach John on the Internet at John@JohnMuellerBooks.com and his Web site at: http://www.johnmuellerbooks.com. Make sure to read his blog at http://blog.johnmuellerbooks.com to obtain the latest book information, updates, and extra materials.
Luca Massaron

Luca Massaron

Luca Massaron is a data scientist and a research director specialized in multivariate statistical analysis, machine learning and customer insight with over a decade of experience in solving real world problems and in generating value for stakeholders by applying reasoning, statistics, data mining and algorithms. From being a pioneer of Web audience analysis in Italy to achieving the rank of top ten data scientist at competitions held by kaggle.com, he has always been passionate about everything regarding data and analysis and about demonstrating the potentiality of data-driven knowledge discovery to both experts and non-experts. Favouring simplicity over unnecessary sophistication, he believes that a lot can be achieved in data science just by doing the essential.
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