Python Algorithms

Author: Magnus Lie Hetland
Publisher: Apress
ISBN: 1484200551
Category : Computers
Languages : en
Pages : 303

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.

Data Structures and Algorithms in Python

Author: Michael T. Goodrich
Publisher: Wiley Global Education
ISBN: 1118476735
Category : Computers
Languages : en
Pages : 770

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.

Problem Solving with Algorithms and Data Structures Using Python

Author: Bradley N. Miller
Publisher: Franklin Beedle & Associates
ISBN: 9781590282571
Category : Algorithms
Languages : en
Pages : 0

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.

Python Algorithms

Author: Magnus Lie Hetland
Publisher: Apress
ISBN: 1430232382
Category : Computers
Languages : en
Pages : 325

Book Description
Python Algorithms 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, but in a highly pedagogic and readable manner. The book 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 himself.

Programming Collective Intelligence

Author: Toby Segaran
Publisher: "O'Reilly Media, Inc."
ISBN: 0596550685
Category : Computers
Languages : en
Pages : 361

Book Description
Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains: Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details." -- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths." -- Tim Wolters, CTO, Collective Intellect

Python Data Structures and Algorithms

Author: Benjamin Baka
Publisher: Packt Publishing Ltd
ISBN: 1786465337
Category : Computers
Languages : en
Pages : 303

Book Description
Implement classic and functional data structures and algorithms using Python About This Book A step by step guide, which will provide you with a thorough discussion on the analysis and design of fundamental Python data structures. Get a better understanding of advanced Python concepts such as big-o notation, dynamic programming, and functional data structures. Explore illustrations to present data structures and algorithms, as well as their analysis, in a clear, visual manner. Who This Book Is For The book will appeal to Python developers. A basic knowledge of Python is expected. What You Will Learn Gain a solid understanding of Python data structures. Build sophisticated data applications. Understand the common programming patterns and algorithms used in Python data science. Write efficient robust code. In Detail Data structures allow you to organize data in a particular way efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. In this book, you will learn the essential Python data structures and the most common algorithms. With this easy-to-read book, you will be able to understand the power of linked lists, double linked lists, and circular linked lists. You will be able to create complex data structures such as graphs, stacks and queues. We will explore the application of binary searches and binary search trees. You will learn the common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. We will also discuss how to organize your code in a manageable, consistent, and extendable way. The book will explore in detail sorting algorithms such as bubble sort, selection sort, insertion sort, and merge sort. By the end of the book, you will learn how to build components that are easy to understand, debug, and use in different applications. Style and Approach The easy-to-read book with its fast-paced nature will improve the productivity of Python programmers and improve the performance of Python applications.

Programming Computer Vision with Python

Author: Jan Erik Solem
Publisher: "O'Reilly Media, Inc."
ISBN: 1449341934
Category : Computers
Languages : en
Pages : 262

Book Description
If you want a basic understanding of computer vision’s underlying theory and algorithms, this hands-on introduction is the ideal place to start. You’ll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, and other computer vision applications as you follow clear examples written in Python. Programming Computer Vision with Python explains computer vision in broad terms that won’t bog you down in theory. You get complete code samples with explanations on how to reproduce and build upon each example, along with exercises to help you apply what you’ve learned. This book is ideal for students, researchers, and enthusiasts with basic programming and standard mathematical skills. Learn techniques used in robot navigation, medical image analysis, and other computer vision applications Work with image mappings and transforms, such as texture warping and panorama creation Compute 3D reconstructions from several images of the same scene Organize images based on similarity or content, using clustering methods Build efficient image retrieval techniques to search for images based on visual content Use algorithms to classify image content and recognize objects Access the popular OpenCV library through a Python interface

Data Structures and Algorithms with Python

Author: Kent D. Lee
Publisher: Springer
ISBN: 3319130722
Category : Computers
Languages : en
Pages : 369

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.

Data Structures & Algorithms in Python

Author: Robert Lafore
Publisher: Addison-Wesley Professional
ISBN: 0134855892
Category : Computers
Languages : en
Pages : 1416

Book Description
LEARN HOW TO USE DATA STRUCTURES IN WRITING HIGH PERFORMANCE PYTHON PROGRAMS AND ALGORITHMS This practical introduction to data structures and algorithms can help every programmer who wants to write more efficient software. Building on Robert Lafore's legendary Java-based guide, this book helps you understand exactly how data structures and algorithms operate. You'll learn how to efficiently apply them with the enormously popular Python language and scale your code to handle today's big data challenges. Throughout, the authors focus on real-world examples, communicate key ideas with intuitive, interactive visualizations, and limit complexity and math to what you need to improve performance. Step-by-step, they introduce arrays, sorting, stacks, queues, linked lists, recursion, binary trees, 2-3-4 trees, hash tables, spatial data structures, graphs, and more. Their code examples and illustrations are so clear, you can understand them even if you're a near-beginner, or your experience is with other procedural or object-oriented languages. Build core computer science skills that take you beyond merely “writing code” Learn how data structures make programs (and programmers) more efficient See how data organization and algorithms affect how much you can do with today's, and tomorrow's, computing resources Develop data structure implementation skills you can use in any language Choose the best data structure(s) and algorithms for each programming problem—and recognize which ones to avoid Data Structures & Algorithms in Python is packed with examples, review questions, individual and team exercises, thought experiments, and longer programming projects. It's ideal for both self-study and classroom settings, and either as a primary text or as a complement to a more formal presentation.

Data Structures and Algorithms Using Python and C++

Author: David M. Reed
Publisher: Franklin Beedle & Associates
ISBN: 9781590282335
Category : Algorithms
Languages : en
Pages : 0

Book Description
This book is intended for use in a traditional college- level data structures course (commonly known as CS2). This book assumes that students have learned the basic syntax of Python and been exposed to the use of existing classes. Most traditional CS1 courses that use Python will have covered all the necessary topics, and some may have covered a few of the topics covered in this book. We have found that most students successfully completing a CS1 course know how to use classes, but many of them need more experience to learn how to design and write their own classes. We address this issue by including a number of examples of class design in the first few chapters of this book.