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Author: Bradley N. Miller
Publisher: Franklin Beedle & Associates
ISBN: 9781590282571
Category : Algorithms
Languages : en
Pages : 0
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Book Description
Thes book has three key features : fundamental data structures and algorithms; algorithm analysis in terms of Big-O running time in introducied early and applied throught; pytohn is used to facilitates the success in using and mastering data strucutes and algorithms.
Author: Bradley N. Miller
Publisher: Franklin Beedle & Associates
ISBN: 9781590282571
Category : Algorithms
Languages : en
Pages : 0
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Book Description
Thes book has three key features : fundamental data structures and algorithms; algorithm analysis in terms of Big-O running time in introducied early and applied throught; pytohn is used to facilitates the success in using and mastering data strucutes and algorithms.
Author: Bradley N. Miller
Publisher:
ISBN:
Category : Computer algorithms
Languages : en
Pages :
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Book Description
Author: Hemant Jain
Publisher: Independently Published
ISBN: 9781098963231
Category :
Languages : en
Pages : 410
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Book Description
"Problem Solving in Data Structures & Algorithms" is a series of books about the usage of Data Structures and Algorithms in computer programming. The book is easy to follow and is written for interview preparation point of view. In these books, the examples are solved in various languages like Go, C, C++, Java, C#, Python, VB, JavaScript and PHP. GitHub Repositories for these books. https: //github.com/Hemant-Jain-Author Book's Composition This book introduces you to the world of data structures and algorithms. Data structures defines the way in which data is arranged in memory for fast and efficient access while algorithms are a set of instruction to solve problems by manipulating these data structures. Designing an efficient algorithm is a very important skill that all software companies, e.g. Microsoft, Google, Facebook etc. pursues. Most of the interviews for these companies are focused on knowledge of data-structures and algorithms. They look for how candidates use concepts of data structures and algorithms to solve complex problems efficiently. Apart from knowing, a programming language you also need to have good command of these key computer fundamentals to not only qualify the interview but also excel in you jobs as a software engineer. This book assumes that you are a C language developer. You are not an expert in C language, but you are well familiar with concepts of classes, functions, arrays, pointers and recursion. At the start of this book, we will be looking into Complexity Analysis followed by the various data structures and their algorithms. We will be looking into a Linked-List, Stack, Queue, Trees, Heap, Hash-Table and Graphs. We will also be looking into Sorting, Searching techniques. In last few chapters, we will be looking into various algorithmic techniques. Such as, Brute-Force algorithms, Greedy algorithms, Divide and Conquer algorithms, Dynamic Programming, Reduction and Backtracking. . Table of Contents Chapter 0: How to use this book. Chapter 1: Algorithms Analysis Chapter 2: Approach to solve algorithm design problems Chapter 3: Abstract Data Type & C# Collections Chapter 4: Searching Chapter 5: Sorting Chapter 6: Linked List Chapter 7: Stack Chapter 8: Queue Chapter 9: Tree Chapter 10: Priority Queue Chapter 11: Hash-Table Chapter 12: Graphs Chapter 13: String Algorithms Chapter 14: Algorithm Design Techniques Chapter 15: Brute Force Algorithm Chapter 16: Greedy Algorithm Chapter 17: Divide & Conquer Chapter 18: Dynamic Programming Chapter 19: Backtracking Chapter 20: Complexity Theory
Author: Michael T. Goodrich
Publisher: Wiley Global Education
ISBN: 1118476735
Category : Computers
Languages : en
Pages : 770
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Book Description
Based on the authors' market leading data structures books in Java and C++, this book offers a comprehensive, definitive introduction to data structures in Python by authoritative authors. Data Structures and Algorithms in Python is the first authoritative object-oriented book available for Python data structures. Designed to provide a comprehensive introduction to data structures and algorithms, including their design, analysis, and implementation, the text will maintain the same general structure as Data Structures and Algorithms in Java and Data Structures and Algorithms in C++. Begins by discussing Python's conceptually simple syntax, which allows for a greater focus on concepts. Employs a consistent object-oriented viewpoint throughout the text. Presents each data structure using ADTs and their respective implementations and introduces important design patterns as a means to organize those implementations into classes, methods, and objects. Provides a thorough discussion on the analysis and design of fundamental data structures. Includes many helpful Python code examples, with source code provided on the website. Uses illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Provides hundreds of exercises that promote creativity, help readers learn how to think like programmers, and reinforce important concepts. Contains many Python-code and pseudo-code fragments, and hundreds of exercises, which are divided into roughly 40% reinforcement exercises, 40% creativity exercises, and 20% programming projects.
Author: Magnus Lie Hetland
Publisher: Apress
ISBN: 1484200551
Category : Computers
Languages : en
Pages : 303
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Book Description
Python Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others.
Author: Mark Allen Weiss
Publisher: Pearson Higher Ed
ISBN: 1292038187
Category : Computers
Languages : en
Pages : 949
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Book Description
For the second or third programming course. A practical and unique approach to data structures that separates interface from implementation. This book provides a practical introduction to data structures with an emphasis on abstract thinking and problem solving, as well as the use of Java. It does this through what remains a unique approach that clearly separates each data structure’s interface (how to use a data structure) from its implementation (how to actually program that structure). Parts I (Tour of Java), II (Algorithms and Building Blocks), and III (Applications) lay the groundwork by discussing basic concepts and tools and providing some practical examples, while Part IV (Implementations) focuses on implementation of data structures. This forces the reader to think about the functionality of the data structures before the hash table is implemented. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.
Author: Hemant Jain
Publisher: Createspace Independent Publishing Platform
ISBN: 9781539724124
Category :
Languages : en
Pages : 436
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Book Description
This book is about the usage of Data Structures and Algorithms in computer programming. Designing an efficient algorithm to solve a computer science problem is a skill of Computer programmer. This is the skill which tech companies like Google, Amazon, Microsoft, Adobe and many others are looking for in an interview. This book assumes that you are a JAVA language developer. You are not an expert in JAVA language, but you are well familiar with concepts of references, functions, lists and recursion. In the start of this book, we will be revising the JAVA language fundamentals. We will be looking into some of the problems in arrays and recursion too. Then in the coming chapter, we will be looking into complexity analysis. Then will look into the various data structures and their algorithms. We will be looking into a Linked List, Stack, Queue, Trees, Heap, Hash Table and Graphs. We will be looking into Sorting & Searching techniques. Then we will be looking into algorithm analysis, we will be looking into Brute Force algorithms, Greedy algorithms, Divide & Conquer algorithms, Dynamic Programming, Reduction, and Backtracking. In the end, we will be looking into System Design, which will give a systematic approach for solving the design problems in an Interview.
Author: Daniel Zingaro
Publisher: No Starch Press
ISBN: 1718501331
Category : Computers
Languages : en
Pages : 392
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Book Description
Learn to Code by Solving Problems is a practical introduction to programming using Python. It uses coding-competition challenges to teach you the mechanics of coding and how to think like a savvy programmer. Computers are capable of solving almost any problem when given the right instructions. That’s where programming comes in. This beginner’s book will have you writing Python programs right away. You’ll solve interesting problems drawn from real coding competitions and build your programming skills as you go. Every chapter presents problems from coding challenge websites, where online judges test your solutions and provide targeted feedback. As you practice using core Python features, functions, and techniques, you’ll develop a clear understanding of data structures, algorithms, and other programming basics. Bonus exercises invite you to explore new concepts on your own, and multiple-choice questions encourage you to think about how each piece of code works. You’ll learn how to: Run Python code, work with strings, and use variables Write programs that make decisions Make code more efficient with while and for loops Use Python sets, lists, and dictionaries to organize, sort, and search data Design programs using functions and top-down design Create complete-search algorithms and use Big O notation to design more efficient code By the end of the book, you’ll not only be proficient in Python, but you’ll also understand how to think through problems and tackle them with code. Programming languages come and go, but this book gives you the lasting foundation you need to start thinking like a programmer.
Author: Kent D. Lee
Publisher: Springer
ISBN: 3319130722
Category : Computers
Languages : en
Pages : 369
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Book Description
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.
Author: David Kopec
Publisher: Simon and Schuster
ISBN: 1638356548
Category : Computers
Languages : en
Pages : 262
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Book Description
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
