Data Structure and Algorithmic Thinking with Python

Author: Narasimha Karumanchi

Publisher: Careermonk Publications

ISBN: 9788192107592


Page: 472

View: 4408


It is the Python version of "Data Structures and Algorithms Made Easy." Table of Contents: Sample Chapter: Source Code: The sample chapter should give you a very good idea of the quality and style of our book. In particular, be sure you are comfortable with the level and with our Python coding style. This book focuses on giving solutions for complex problems in data structures and algorithm. It even provides multiple solutions for a single problem, thus familiarizing readers with different possible approaches to the same problem. "Data Structure and Algorithmic Thinking with Python" is designed to give a jump-start to programmers, job hunters and those who are appearing for exams. All the code in this book are written in Python. It contains many programming puzzles that not only encourage analytical thinking, but also prepares readers for interviews. This book, with its focused and practical approach, can help readers quickly pick up the concepts and techniques for developing efficient and effective solutions to problems. Topics covered include: Organization of Chapters Introduction Recursion and Backtracking Linked Lists Stacks Queues Trees Priority Queues and Heaps Disjoint Sets ADT Graph Algorithms Sorting Searching Selection Algorithms [Medians] Symbol Tables Hashing String Algorithms Algorithms Design Techniques Greedy Algorithms Divide and Conquer Algorithms Dynamic Programming Complexity Classes Hacks on Bit-wise Programming Other Programming Questions

Data Structures and Algorithms with Python

Author: Kent D. Lee,Steve Hubbard

Publisher: Springer

ISBN: 3319130722

Category: Computers

Page: 363

View: 6253


This textbook explains the concepts and techniques required to write programs that can handle large amounts of data efficiently. Project-oriented and classroom-tested, the book presents a number of important algorithms supported by examples that bring meaning to the problems faced by computer programmers. The idea of computational complexity is also introduced, demonstrating what can and cannot be computed efficiently so that the programmer can make informed judgements about the algorithms they use. Features: includes both introductory and advanced data structures and algorithms topics, with suggested chapter sequences for those respective courses provided in the preface; provides learning goals, review questions and programming exercises in each chapter, as well as numerous illustrative examples; offers downloadable programs and supplementary files at an associated website, with instructor materials available from the author; presents a primer on Python for those from a different language background.

Handbook of Research on Immersive Digital Games in Educational Environments

Author: Krassmann, Aliane Loureiro,Amaral, Érico Marcelo Hoff do,Nunes, Felipe Becker,Voss, Gleizer Bierhalz,Zunguze, Manuel Constantino

Publisher: IGI Global

ISBN: 1522557911

Category: Education

Page: 695

View: 3023


Education is increasingly being involved with technological resources in order to meet the needs of emerging generations, consequently changing the way people teach and learn. Game-based learning is a growing aspect of pedagogical practice, and it is important to disseminate research trends and innovations in this field. The Handbook of Research on Immersive Digital Games in Educational Environments provides emerging research exploring the theoretical and practical aspects of digital games and technological resources and applications within contemporary education. Featuring coverage on a broad range of topics such as digital integration, educational simulation, and learning theories, this book is ideally designed for teachers, pre-service teachers, students, educational researchers, and education software developers seeking current research on diverse immersive platforms and three-dimensional environments that support the creation of digital games and other applications to improve teaching and learning processes.

Essential Algorithms

A Practical Approach to Computer Algorithms Using Python and C#

Author: Rod Stephens

Publisher: John Wiley & Sons

ISBN: 1119575990

Category: Computers

Page: 800

View: 8909


A friendly introduction to the most useful algorithms written in simple, intuitive English The revised and updated second edition of Essential Algorithms, offers an accessible introduction to computer algorithms. The book contains a description of important classical algorithms and explains when each is appropriate. The author shows how to analyze algorithms in order to understand their behavior and teaches techniques that the can be used to create new algorithms to meet future needs. The text includes useful algorithms such as: methods for manipulating common data structures, advanced data structures, network algorithms, and numerical algorithms. It also offers a variety of general problem-solving techniques. In addition to describing algorithms and approaches, the author offers details on how to analyze the performance of algorithms. The book is filled with exercises that can be used to explore ways to modify the algorithms in order to apply them to new situations. This updated edition of Essential Algorithms: Contains explanations of algorithms in simple terms, rather than complicated math Steps through powerful algorithms that can be used to solve difficult programming problems Helps prepare for programming job interviews that typically include algorithmic questions Offers methods can be applied to any programming language Includes exercises and solutions useful to both professionals and students Provides code examples updated and written in Python and C# Essential Algorithms has been updated and revised and offers professionals and students a hands-on guide to analyzing algorithms as well as the techniques and applications. The book also includes a collection of questions that may appear in a job interview. The book’s website will include reference implementations in Python and C# (which can be easily applied to Java and C++).