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Learning Algorithms - 9781492091066

Description: Learning Algorithms Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). A Programmer's Guide to Writing Better Code Author(s): George Heineman Format: Paperback Publisher: O'Reilly Media, United States Imprint: O'Reilly Media ISBN-13: 9781492091066, 978-1492091066 Synopsis When it comes to writing efficient code, every software professional needs to have an effective working knowledge of algorithms. In this practical book, author George Heineman (Algorithms in a Nutshell) provides concise and informative descriptions of key algorithms that improve coding. Software developers, testers, and maintainers will discover how algorithms solve computational problems creatively. Each chapter builds on earlier chapters through eye-catching visuals and a steady rollout of essential concepts, including an algorithm analysis to classify the performance of every algorithm presented in the book. At the end of each chapter, you'll get to apply what you've learned to a novel challenge problem -- simulating the experience you might find in a technical code interview. With this book, you will: Examine fundamental algorithms central to computer science and software engineering Learn common strategies for efficient problem solving -- such as divide and conquer, dynamic programming, and greedy approaches Analyze code to evaluate time complexity using big O notation Use existing Python libraries and data structures to solve problems using algorithms Understand the main steps of important algorithms

Price: 45.72 GBP

Location: Aldershot

End Time: 2025-01-13T11:10:32.000Z

Shipping Cost: 28.92 GBP

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Learning Algorithms - 9781492091066

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Book Title: Learning Algorithms

Item Height: 233 mm

Item Width: 178 mm

Author: George Heineman

Publication Name: Learning Algorithms: a Programmer's Guide to Writing Better Code

Format: Paperback

Language: English

Publisher: O'reilly Media, INC International Concepts USA

Subject: Computer Science

Publication Year: 2021

Type: Textbook

Number of Pages: 350 Pages

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