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Classic Computer Science Problems in Java

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Release : 2020-12-21
Genre : Computers
Kind : eBook
Book Rating : 548/5 ( reviews)

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Book Synopsis Classic Computer Science Problems in Java by : David Kopec

Download or read book Classic Computer Science Problems in Java written by David Kopec. This book was released on 2020-12-21. Available in PDF, EPUB and Kindle. Book excerpt: 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. You’ll 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 you’re 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. You’ll 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

Python Programming

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Author :
Release : 2004
Genre : Computers
Kind : eBook
Book Rating : 996/5 ( reviews)

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Book Synopsis Python Programming by : John M. Zelle

Download or read book Python Programming written by John M. Zelle. This book was released on 2004. Available in PDF, EPUB and Kindle. Book excerpt: This book is suitable for use in a university-level first course in computing (CS1), as well as the increasingly popular course known as CS0. It is difficult for many students to master basic concepts in computer science and programming. A large portion of the confusion can be blamed on the complexity of the tools and materials that are traditionally used to teach CS1 and CS2. This textbook was written with a single overarching goal: to present the core concepts of computer science as simply as possible without being simplistic.

Learning Scientific Programming with Python

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Release : 2016-02-04
Genre : Science
Kind : eBook
Book Rating : 223/5 ( reviews)

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Book Synopsis Learning Scientific Programming with Python by : Christian Hill

Download or read book Learning Scientific Programming with Python written by Christian Hill. This book was released on 2016-02-04. Available in PDF, EPUB and Kindle. Book excerpt: Learn to master basic programming tasks from scratch with real-life scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to quickly gain proficiency. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving onto the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualisation, this textbook also discusses the use of IPython notebooks to build rich-media, shareable documents for scientific analysis. Including a final chapter introducing challenging topics such as floating-point precision and algorithm stability, and with extensive online resources to support advanced study, this textbook represents a targeted package for students requiring a solid foundation in Python programming.

Dart for Absolute Beginners

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Release : 2014-06-30
Genre : Computers
Kind : eBook
Book Rating : 829/5 ( reviews)

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Book Synopsis Dart for Absolute Beginners by : David Kopec

Download or read book Dart for Absolute Beginners written by David Kopec. This book was released on 2014-06-30. Available in PDF, EPUB and Kindle. Book excerpt: Dart for Absolute Beginners enables individuals with no background in programming to create their own web apps while learning the fundamentals of software development in a cutting edge language. Easily digested chapters, while comprehensive enough to explore the whole domain, are aimed at both hobbyists and professionals alike. The reader will not only gain an insight into Dart, but also the technologies behind the web. A firm foundation is laid for further programming studies. Dart is a new, innovative language developed by Google which is poised to take the web by storm. For client side web app development, Dart has many advantages over JavaScript. These include but are not limited to: improved speed, enforcement of programmatic structure, and improved facilities for software reuse. Best of all, Dart is automatically converted to JavaScript so that it works with all web browsers. Dart is a fresh start, without the baggage of the last two decades of the web. Why start learning to program with yesterday’s technology? Teaches you the fundamentals of programming and the technologies behind the web. Utilizes the cutting edge, easy to learn, structured Dart programming language so that your first steps are pointed towards the future of web development. No prior knowledge is required to begin developing your own web apps.

Introduction to Computation and Programming Using Python, second edition

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Author :
Release : 2016-08-12
Genre : Computers
Kind : eBook
Book Rating : 629/5 ( reviews)

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Book Synopsis Introduction to Computation and Programming Using Python, second edition by : John V. Guttag

Download or read book Introduction to Computation and Programming Using Python, second edition written by John V. Guttag. This book was released on 2016-08-12. Available in PDF, EPUB and Kindle. Book excerpt: The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.

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