Sinopsis
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
"Sinopsis" puede pertenecer a otra edición de este libro.
Acerca del autor
George Heineman is a professor of computer science with over twenty years of experience in software engineering and algorithms. He is the author of Algorithms in a Nutshell (2ed) and numerous Safari live training offerings, including Exploring Algorithms in Python and Working with Algorithms in Python.
"Sobre este título" puede pertenecer a otra edición de este libro.
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Learning Algorithms: A Programmer's Guide to Writing Better Code
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Paperback. Condición: New. 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 engineeringLearn common strategies for efficient problem solving -- such as divide and conquer, dynamic programming, and greedy approachesAnalyze code to evaluate time complexity using big O notationUse existing Python libraries and data structures to solve problems using algorithmsUnderstand the main steps of important algorithms. Nº de ref. del artículo: LU-9781492091066
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Paperback. Condición: new. Paperback. 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 in multiple languages. 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, youa??ll get to apply what youa??ve learned to a novel challenge problema??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 engineeringLearn common strategies for efficient problem solvinga??such as divide and conquer, dynamic programming, and greedy approachesAnalyze code to evaluate time complexity using big O notationUse existing Python libraries and data structures to solve problems using algorithmsUnderstand the main steps of important algorithmsAbout the AuthorGeorge Heineman is a professor of computer science with over twenty years of experience in software engineering and algorithms. He is the author of Algorithms in a Nutshell (2ed) and numerous Safari live training offerings, including Exploring Algorithms in Python and Working with Algorithms in Python. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781492091066
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Learning Algorithms
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Paperback. Condición: New. 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 engineeringLearn common strategies for efficient problem solving -- such as divide and conquer, dynamic programming, and greedy approachesAnalyze code to evaluate time complexity using big O notationUse existing Python libraries and data structures to solve problems using algorithmsUnderstand the main steps of important algorithms. Nº de ref. del artículo: LU-9781492091066
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