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Generic data structures and algorith...

Wiener, Richard.

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Generic data structures and algorithms in Go = an applied approach using concurrency, genericity and heuristics /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Generic data structures and algorithms in Go/ by Richard Wiener.
Reminder of title:	an applied approach using concurrency, genericity and heuristics /
Author:	Wiener, Richard.
Published:	Berkeley, CA :Apress : : 2022.,
Description:	xxv, 579 p. :ill., digital ;24 cm.
[NT 15003449]:	1. A Tour Of Generics and Concurrency In Go -- 2. Algorithm Efficiency - Sorting and Searching -- 3. Abstract Data Types: OOP Without Classes in Go -- 4. ADT In Action: Game Of Life -- 5. Stacks -- 6. Queues and Lists -- 7. Hash Tables -- 8. Binary Trees -- 9. Binary Search Tree -- 10. AVL Trees -- 11. Heap Trees -- 12. Red Black Trees -- 13. Expression Trees -- 14. Ecological Simulation With Concurrency -- 15. Dynamic Programming -- 16. Graph Structures -- 17. Travelling Salesperson Problem -- 18. Branch and Bound Solution to TSP -- 19. Simulated Annealing Heuristic Solution to TSP -- 20. Genetic Algorithm for TSP -- 21. Neural Networks and Machine Learning.
Contained By:	Springer Nature eBook
Subject:	Go (Computer program language) -
Online resource:	https://doi.org/10.1007/978-1-4842-8191-8
ISBN:	9781484281918

Generic data structures and algorithms in Go = an applied approach using concurrency, genericity and heuristics /
Wiener, Richard.

Generic data structures and algorithms in Goan applied approach using concurrency, genericity and heuristics /[electronic resource] :by Richard Wiener. - Berkeley, CA :Apress :2022. - xxv, 579 p. :ill., digital ;24 cm.

1. A Tour Of Generics and Concurrency In Go -- 2. Algorithm Efficiency - Sorting and Searching -- 3. Abstract Data Types: OOP Without Classes in Go -- 4. ADT In Action: Game Of Life -- 5. Stacks -- 6. Queues and Lists -- 7. Hash Tables -- 8. Binary Trees -- 9. Binary Search Tree -- 10. AVL Trees -- 11. Heap Trees -- 12. Red Black Trees -- 13. Expression Trees -- 14. Ecological Simulation With Concurrency -- 15. Dynamic Programming -- 16. Graph Structures -- 17. Travelling Salesperson Problem -- 18. Branch and Bound Solution to TSP -- 19. Simulated Annealing Heuristic Solution to TSP -- 20. Genetic Algorithm for TSP -- 21. Neural Networks and Machine Learning.

Advance your understanding of generic data structures and algorithms and their applications using Go and the effective use of concurrency. You are invited on a journey that aims to improve your programming and problem-solving skills. This book takes you to the next step by showing how to get your programs to work efficiently as well as correctly. As you explore many data structures and the algorithms and applications associated with them, you'll focus on the trade-offs between speed and storage and the benefits of deploying concurrency when appropriate. This book will demonstrate the huge increases in application performance that are possible. The presentation of classic data structures and techniques of algorithm design (greedy, divide and conquer, branch-and-bound to name a few) provides an essential foundation and toolkit for problem solving. But this book goes further by presenting heuristic algorithms and their implementations for solving computationally intractable combinatoric optimization problems such as the travelling salesperson problem. Simulated annealing and genetic algorithms are among the techniques used. The consistent style of coding used throughout this book exploits Go's ability to implement abstract, generic and constrained generic data types without the use of classes. Although some familiarity with Go is assumed, this book should advance your ability to use Go to tackle server-side applications, games, machine learning, information retrieval and other application domains where speed and storage efficiency is essential. You will: Explore classical data structures and algorithms aimed at making your applications run faster or require less storage Use the new generic features of Go to build reusable data structures Utilize concurrency for maximizing application performance See the power of heuristic algorithms for computationally intractable problems Enhance and improve your Go programming skills.

ISBN: 9781484281918

Standard No.: 10.1007/978-1-4842-8191-8doiSubjects--Topical Terms:

2165707
Go (Computer program language)

LC Class. No.: QA76.9.D35 / W54 2022

Dewey Class. No.: 005.133

Generic data structures and algorithms in Go = an applied approach using concurrency, genericity and heuristics /
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245 1 0 $a Generic data structures and algorithms in Go $h [electronic resource] : $b an applied approach using concurrency, genericity and heuristics / $c by Richard Wiener.
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505 0 $a 1. A Tour Of Generics and Concurrency In Go -- 2. Algorithm Efficiency - Sorting and Searching -- 3. Abstract Data Types: OOP Without Classes in Go -- 4. ADT In Action: Game Of Life -- 5. Stacks -- 6. Queues and Lists -- 7. Hash Tables -- 8. Binary Trees -- 9. Binary Search Tree -- 10. AVL Trees -- 11. Heap Trees -- 12. Red Black Trees -- 13. Expression Trees -- 14. Ecological Simulation With Concurrency -- 15. Dynamic Programming -- 16. Graph Structures -- 17. Travelling Salesperson Problem -- 18. Branch and Bound Solution to TSP -- 19. Simulated Annealing Heuristic Solution to TSP -- 20. Genetic Algorithm for TSP -- 21. Neural Networks and Machine Learning.
520 $a Advance your understanding of generic data structures and algorithms and their applications using Go and the effective use of concurrency. You are invited on a journey that aims to improve your programming and problem-solving skills. This book takes you to the next step by showing how to get your programs to work efficiently as well as correctly. As you explore many data structures and the algorithms and applications associated with them, you'll focus on the trade-offs between speed and storage and the benefits of deploying concurrency when appropriate. This book will demonstrate the huge increases in application performance that are possible. The presentation of classic data structures and techniques of algorithm design (greedy, divide and conquer, branch-and-bound to name a few) provides an essential foundation and toolkit for problem solving. But this book goes further by presenting heuristic algorithms and their implementations for solving computationally intractable combinatoric optimization problems such as the travelling salesperson problem. Simulated annealing and genetic algorithms are among the techniques used. The consistent style of coding used throughout this book exploits Go's ability to implement abstract, generic and constrained generic data types without the use of classes. Although some familiarity with Go is assumed, this book should advance your ability to use Go to tackle server-side applications, games, machine learning, information retrieval and other application domains where speed and storage efficiency is essential. You will: Explore classical data structures and algorithms aimed at making your applications run faster or require less storage Use the new generic features of Go to build reusable data structures Utilize concurrency for maximizing application performance See the power of heuristic algorithms for computationally intractable problems Enhance and improve your Go programming skills.
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