Grokking Algorithms Book [PDF] Download

Download the fantastic book titled Grokking Algorithms written by Aditya Bhargava, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Grokking Algorithms", which was released on 12 May 2016. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Grokking Algorithms by Aditya Bhargava PDF

"This book does the impossible: it makes math fun and easy!" - Sander Rossel, COAS Software Systems Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. Learning about algorithms doesn't have to be boring! Get a sneak peek at the fun, illustrated, and friendly examples you'll find in Grokking Algorithms on Manning Publications' YouTube channel. Continue your journey into the world of algorithms with Algorithms in Motion, a practical, hands-on video course available exclusively at Manning.com (www.manning.com/livevideo/algorithms-?in-motion). Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology An algorithm is nothing more than a step-by-step procedure for solving a problem. The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to understand them but refuse to slog through dense multipage proofs, this is the book for you. This fully illustrated and engaging guide makes it easy to learn how to use the most important algorithms effectively in your own programs. About the Book Grokking Algorithms is a friendly take on this core computer science topic. In it, you'll learn how to apply common algorithms to the practical programming problems you face every day. You'll start with tasks like sorting and searching. As you build up your skills, you'll tackle more complex problems like data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. By the end of this book, you will have mastered widely applicable algorithms as well as how and when to use them. What's Inside Covers search, sort, and graph algorithms Over 400 pictures with detailed walkthroughs Performance trade-offs between algorithms Python-based code samples About the Reader This easy-to-read, picture-heavy introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. About the Author Aditya Bhargava is a Software Engineer with a dual background in Computer Science and Fine Arts. He blogs on programming at adit.io. Table of Contents Introduction to algorithms Selection sort Recursion Quicksort Hash tables Breadth-first search Dijkstra's algorithm Greedy algorithms Dynamic programming K-nearest neighbors


Detail About Grokking Algorithms PDF

  • Author : Aditya Bhargava
  • Publisher : Simon and Schuster
  • Genre : Computers
  • Total Pages : 354 pages
  • ISBN : 1638353344
  • PDF File Size : 32,7 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Grokking Algorithms

Grokking Algorithms
  • Publisher : Simon and Schuster
  • File Size : 45,6 Mb
  • Release Date : 12 May 2016
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"This book does the impossible: it makes math fun and easy!" - Sander Rossel, COAS Software Systems Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to

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Grokking Artificial Intelligence Algorithms
  • Publisher : Simon and Schuster
  • File Size : 47,6 Mb
  • Release Date : 20 July 2020
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"From start to finish, the best book to help you learn AI algorithms and recall why and how you use them." - Linda Ristevski, York Region District School Board ”This

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Grokking Deep Learning
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Summary Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the

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Grokking Machine Learning
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  • File Size : 55,8 Mb
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Grokking Machine Learning presents machine learning algorithms and techniques in a way that anyone can understand. This book skips the confused academic jargon and offers clear explanations that require only

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Distributed across servers, difficult to test, and resistant to modification--modern software is complex. Grokking Simplicity is a friendly, practical guide that will change the way you approach software design and

Grokking Functional Programming

Grokking Functional Programming
  • Publisher : Simon and Schuster
  • File Size : 34,7 Mb
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There’s no need to fear going functional! This friendly, lively, and engaging guide is perfect for any perplexed programmer. It lays out the principles of functional programming in a

Computer Science Distilled

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  • File Size : 26,6 Mb
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A foolproof walkthrough of must-know computer science concepts. A fast guide for those who don't need the academic formality, it goes straight to what differentiates pros from amateurs. First introducing

A Common-Sense Guide to Data Structures and Algorithms

A Common-Sense Guide to Data Structures and Algorithms
  • Publisher : Pragmatic Bookshelf
  • File Size : 26,9 Mb
  • Release Date : 03 August 2017
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" Algorithms and data structures are much more than abstract concepts. Mastering them enables you to write code that runs faster and more efficiently, which is particularly important for today’s

Grokking Deep Reinforcement Learning

Grokking Deep Reinforcement Learning
  • Publisher : Manning Publications
  • File Size : 44,5 Mb
  • Release Date : 10 November 2020
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Grokking Deep Reinforcement Learning uses engaging exercises to teach you how to build deep learning systems. This book combines annotated Python code with intuitive explanations to explore DRL techniques. You’