Competitive Programming in Python (128 Algorithms to Develop your Coding Skills)
معرفی کتاب «Competitive Programming in Python (128 Algorithms to Develop your Coding Skills)» نوشتهٔ Christoph Dürr; Jill-Jênn Vie; Greg Gibbons; Danièle Gibbons; Cambridge University Press، منتشرشده توسط نشر University of Cambridge ESOL Examinations; Cambridge University Press در سال 2021. این کتاب در فرمت pdf، زبان انگلیسی ارائه شده است. «Competitive Programming in Python (128 Algorithms to Develop your Coding Skills)» در دستهٔ بدون دستهبندی قرار دارد.
Want to kill it at your job interview in the tech industry? Want to win that coding competition? Learn all the algorithmic techniques and programming skills you need from two experienced coaches, problem setters, and jurors for coding competitions. The authors highlight the versatility of each algorithm by considering a variety of problems and show how to implement algorithms in simple and efficient code. Readers can expect to master 128 algorithms in Python and discover the right way to tackle a problem and quickly implement a solution of low complexity. Classic problems like Dijkstra's shortest path algorithm and Knuth-Morris-Pratt's string matching algorithm are featured alongside lesser known data structures like Fenwick trees and Knuth's dancing links. The book provides a framework to tackle algorithmic problem solving, including: Definition, Complexity, Applications, Algorithm, Key Information, Implementation, Variants, In Practice, and Problems. Python code included in the book and on the companion website. "Want to kill it at your job interview in the tech industry? Want to win that coding competition? Learn all the algorithmic techniques and programming skills you need from two experienced coaches, problem setters, and jurors for coding competitions. The authors highlight the versatility of each algorithm by considering a variety of problems and show how to implement algorithms in simple and efficient code. What to expect: * Master 128 algorithms in Python. * Discover the right way to tackle a problem and quickly implement a solution of low complexity. * Classic problems like Dijkstra's shortest path algorithm and Knuth-Morris-Pratt's string matching algorithm, plus lesser known data structures like Fenwick trees and Knuth's dancing links. * A framework to tackle algorithmic problem solving, including: Definition, Complexity, Applications, Algorithm, Key Information, Implementation, Variants, In Practice, and Problems. * Python code in the book and on the companion website"-- Provided by publisher
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