Sharpen your coding skills by exploring established computer science problems! Classic Computer Science Problems in Java challenges you with time-tested scenarios and algorithms.
Summary
Sharpen your coding skills by exploring established computer science problems! Classic Computer Science Problems in Java challenges you with time-tested scenarios and algorithms. Youll work through a series of exercises based in computer science fundamentals that are designed to improve your software development abilities, improve your understanding of artificial intelligence, and even prepare you to ace an interview. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your "new" problems!
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
Whatever software development problem youre facing, odds are someone has already uncovered a solution. This book collects the most useful solutions devised, guiding you through a variety of challenges and tried-and-true problem-solving techniques. The principles and algorithms presented here are guaranteed to save you countless hours in project after project.
About the book
Classic Computer Science Problems in Java is a master class in computer programming designed around 55 exercises that have been used in computer science classrooms for years. Youll work through hands-on examples as you explore core algorithms, constraint problems, AI applications, and much more.
What's inside
Recursion, memoization, and bit manipulation
Search, graph, and genetic algorithms
Constraint-satisfaction problems
K-means clustering, neural networks, and adversarial search
About the reader
For intermediate Java programmers.
About the author
David Kopec is an assistant professor of Computer Science and Innovation at Champlain College in Burlington, Vermont.
Table of Contents
1 Small problems
2 Search problems
3 Constraint-satisfaction problems
4 Graph problems
5 Genetic algorithms
6 K-means clustering
7 Fairly simple neural networks
8 Adversarial search
9 Miscellaneous problems
10 Interview with Brian Goetz

nexusstc/Classic Computer Science Problems in Java/cf9c8afa92f2c825ecf63f0783291e86.pdf

lgrsnf/1617297607.pdf

zlib/Computers/Programming/David Kopec/Classic Computer Science Problems in Java_11064954.pdf

Классические задачи Computer Science на языке Java: 16+

Дэвид Копец; [перевел с английского А. Павлов]

Kopec, David

Копец, Дэвид

Manning Publications Co. LLC

Питер

Серия "Библиотека программиста", Санкт-Петербург [и др.], Russia, 2022

United States, United States of America

Simon & Schuster, Shelter Island, 2020

Shelter Island, NY, 2020

New York, 2021

PS, 2021

lg2891789

{"isbns":["1617297607","9781617297601"],"last_page":264,"publisher":"Manning"}

Фактическая дата выхода в свет - 2021
Библиогр.: с. 284-287
Пер.: Kopec, David Classic computer science problems in Java Shelter Island : Manning, 2020 978-1617297601

РГБ

Russian State Library [rgb] MARC:
=001 010913589
=005 20211213165009.0
=008 211202s2022\\\\ru\\\\\\\\\\\\000\|\rus|d
=017 \\ $a КН-П-21-085171 $b RuMoRKP
=020 \\ $a 978-5-4461-3911-8 $c 1000 экз.
=040 \\ $a RuMoRKP $b rus $e rcr $d RuMoRGB
=041 1\ $a rus $h eng
=044 \\ $a ru
=080 \\ $a 004.438 $2 4
=084 \\ $a З973.26-018.19Java,07 $2 rubbk
=100 1\ $a Копец, Дэвид
=245 00 $a Классические задачи Computer Science на языке Java : $b 16+ $c Дэвид Копец ; [перевел с английского А. Павлов]
=260 \\ $a Санкт-Петербург [и др.] $b Питер $c 2022
=300 \\ $a 287 с. $b ил. $c 23 см
=336 \\ $a Текст (визуальный)
=337 \\ $a непосредственный
=490 0\ $a Серия "Библиотека программиста"
=500 \\ $a Фактическая дата выхода в свет - 2021
=504 \\ $a Библиогр.: с. 284-287
=520 \\ $a Столкнулись с неразрешимой проблемой при разработке программного обеспечения? Скорее всего, кто-то уже справился с этой задачей, и вы можете не ломать голову. Дэвид Копец собрал наиболее полезные готовые решения, принципы и алгоритмы. - это мастер-класс по программированию, содержащий 55 практических примеров, затрагивающих самые актуальные темы: базовые алгоритмы, ограничения, искусственный интеллект и многое другое
=534 \\ $p Пер.: $a Kopec, David $t Classic computer science problems in Java $c Shelter Island : Manning, 2020 $z 978-1617297601
=650 \7 $a Программирования языки объектно-ориентированные $2 RuMoRKP
=650 \7 $a Техника. Технические науки -- Энергетика. Радиоэлектроника -- Радиоэлектроника -- Вычислительная техника -- Вычислительные машины электронные цифровые -- Персональные компьютеры -- Программирование -- Языки программирования -- Java -- Пособие для специалистов
=653 \\ $a Java
=852 \\ $a РГБ $b FB $j 2 21-66/282 $x 90
=852 7\ $a РГБ $b CZ2 $h З973.2-018/К65 $x 83

Classic Computer Science Problems in Java
brief contents
contents
acknowledgments
about this book
liveBook discussion forum
about the author
about the cover illustration
Introduction
Who should read this book
How this book is organized: A roadmap
About the code
Other online resources
1 Small problems
1.1 The Fibonacci sequence
1.1.1 A first recursive attempt
1.1.2 Utilizing base cases
1.1.3 Memoization to the rescue
1.1.4 Keep it simple, Fibonacci
1.1.5 Generating Fibonacci numbers with a stream
1.2 Trivial compression
1.3 Unbreakable encryption
1.3.1 Getting the data in order
1.3.2 Encrypting and decrypting
1.4 Calculating pi
1.5 The Towers of Hanoi
1.5.1 Modeling the towers
1.5.2 Solving The Towers of Hanoi
1.6 Real-world applications
1.7 Exercises
2 Search problems
2.1 DNA search
2.1.1 Storing DNA
2.1.2 Linear search
2.1.3 Binary search
2.1.4 A generic example
2.2 Maze solving
2.2.1 Generating a random maze
2.2.2 Miscellaneous maze minutiae
2.2.3 Depth-first search
2.2.4 Breadth-first search
2.2.5 A* search
2.3 Missionaries and cannibals
2.3.1 Representing the problem
2.3.2 Solving
2.4 Real-world applications
2.5 Exercises
3 Constraint-satisfaction problems
3.1 Building a constraint-satisfaction problem framework
3.2 The Australian map-coloring problem
3.3 The eight queens problem
3.4 Word search
3.5 SEND+MORE=MONEY
3.6 Circuit board layout
3.7 Real-world applications
3.8 Exercises
4 Graph problems
4.1 A map as a graph
4.2 Building a graph framework
4.2.1 Working with Edge and UnweightedGraph
4.3 Finding the shortest path
4.3.1 Revisiting breadth-first search (BFS)
4.4 Minimizing the cost of building the network
4.4.1 Working with weights
4.4.2 Finding the minimum spanning tree
4.5 Finding shortest paths in a weighted graph
4.5.1 Dijkstra’s algorithm
4.6 Real-world applications
4.7 Exercises
5 Genetic algorithms
5.1 Biological background
5.2 A generic genetic algorithm
5.3 A naive test
5.4 SEND+MORE=MONEY revisited
5.5 Optimizing list compression
5.6 Challenges for genetic algorithms
5.7 Real-world applications
5.8 Exercises
6 K-means clustering
6.1 Preliminaries
6.2 The k-means clustering algorithm
6.3 Clustering governors by age and longitude
6.4 Clustering Michael Jackson albums by length
6.5 K-means clustering problems and extensions
6.6 Real-world applications
6.7 Exercises
7 Fairly simple neural networks
7.1 Biological basis?
7.2 Artificial neural networks
7.2.1 Neurons
7.2.2 Layers
7.2.3 Backpropagation
7.2.4 The big picture
7.3 Preliminaries
7.3.1 Dot product
7.3.2 The activation function
7.4 Building the network
7.4.1 Implementing neurons
7.4.2 Implementing layers
7.4.3 Implementing the network
7.5 Classification problems
7.5.1 Normalizing data
7.5.2 The classic iris data set
7.5.3 Classifying wine
7.6 Speeding up neural networks
7.7 Neural network problems and extensions
7.8 Real-world applications
7.9 Exercises
8 Adversarial search
8.1 Basic board game components
8.2 Tic-tac-toe
8.2.1 Managing tic-tac-toe state
8.2.2 Minimax
8.2.3 Testing minimax with tic-tac-toe
8.2.4 Developing a tic-tac-toe AI
8.3 Connect Four
8.3.1 Connect Four game machinery
8.3.2 A Connect Four AI
8.3.3 Improving minimax with alpha-beta pruning
8.4 Minimax improvements beyond alpha-beta pruning
8.5 Real-world applications
8.6 Exercises
9 Miscellaneous problems
9.1 The knapsack problem
9.2 The Traveling Salesman Problem
9.2.1 The naive approach
9.2.2 Taking it to the next level
9.3 Phone number mnemonics
9.4 Real-world applications
9.5 Exercises
10 Interview with Brian Goetz
Appendix A—Glossary
Appendix B—More resources
Java
Data structures and algorithms
Artificial intelligence
Functional programming
index
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
Q
R
S
T
U
V
W
X
Z

**Sharpen your coding skills by exploring established computer science problems! __Classic Computer Science Problems in Java__ challenges you with time-tested scenarios and algorithms.****Summary**__Classic Computer Science Problems in Java__**About the technology****About the book**__Classic Computer Science Problems in Java__**What's inside****About the reader****About the author****David Kopec****Table of Contents**

Столкнулись с неразрешимой проблемой при разработке программного обеспечения? Скорее всего, кто-то уже справился с этой задачей, и вы можете не ломать голову. Дэвид Копец собрал наиболее полезные готовые решения, принципы и алгоритмы. - это мастер-класс по программированию, содержащий 55 практических примеров, затрагивающих самые актуальные темы: базовые алгоритмы, ограничения, искусственный интеллект и многое другое

This book is a master class in computer programming designed around 55 exercises that have been used in computer science classrooms for years. Youll work through hands-on examples as you explore core algorithms, constraint problems, AI applications, and much more. -- Edited summary from book

2020-12-23