Python for Informatics

Exploring Information

Author: Charles Severance

Publisher: CreateSpace

ISBN: 9781492339243

Category: Computers

Page: 244

View: 1354

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This book is designed to introduce students to programming and computational thinking through the lens of exploring data. You can think of Python as your tool to solve problems that are far beyond the capability of a spreadsheet. It is an easy-to-use and easy-to learn programming language that is freely available on Windows, Macintosh , and Linux computers. There are free downloadable copies of this book in various electronic formats and a self-paced free online course where you can explore the course materials. All the supporting materials for the book are available under open and remixable licenses. This book is designed to teach people to program even if they have no prior experience.
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Elements of Programming Interviews in Python

Author: Adnan Aziz,Tsung-Hsien Lee,Amit Prakash

Publisher: EPI

ISBN: N.A

Category: Computers

Page: N.A

View: 6101

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Have you ever... - Wanted to work at an exciting futuristic company? - Struggled with an interview problem that could have been solved in 15 minutes? - Wished you could study real-world computing problems? If so, you need to read Elements of Programming Interviews (EPI). EPI is your comprehensive guide to interviewing for software development roles. The core of EPI is a collection of over 250 problems with detailed solutions. The problems are representative of interview questions asked at leading software companies. The problems are illustrated with 200 figures, 300 tested programs, and 150 additional variants. The book begins with a summary of the nontechnical aspects of interviewing, such as strategies for a great interview, common mistakes, perspectives from the other side of the table, tips on negotiating the best offer, and a guide to the best ways to use EPI. We also provide a summary of data structures, algorithms, and problem solving patterns. Coding problems are presented through a series of chapters on basic and advanced data structures, searching, sorting, algorithm design principles, and concurrency. Each chapter stars with a brief introduction, a case study, top tips, and a review of the most important library methods. This is followed by a broad and thought-provoking set of problems. A practical, fun approach to computer science fundamentals, as seen through the lens of common programming interview questions. Jeff Atwood/Co-founder, Stack Overflow and Discourse
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Big Data and Social Science

A Practical Guide to Methods and Tools

Author: Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane

Publisher: CRC Press

ISBN: 1498751431

Category: Mathematics

Page: 376

View: 7316

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Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.
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The Librarian's Introduction to Programming Languages

A LITA Guide

Author: Beth Thomsett-Scott

Publisher: Rowman & Littlefield

ISBN: 1442263342

Category: Language Arts & Disciplines

Page: 200

View: 2593

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The Librarian’s Introduction to Programming Languages presents case studies and practical applications for using the top programming languages in library and information settings. While there are books and Web sites devoted to teaching programming, there are few works that address multiple programming languages or address the specific reasons why programming is a critical area of learning for library and information science professionals. There are many books on programming languages but no recent items directly written for librarians that span a variety of programs. Many practicing librarians see programming as something for IT people or beyond their capabilities. This book will help these librarians to feel comfortable discussing programming with others by providing an understanding of when the language might be useful, what is needed to make it work, and relevant tools to extend its application. Additionally, the inclusion of practical examples lets readers try a small “app” for the language. This also will assist readers who want to learn a language but are unsure of which language would be the best fit for them in terms of learning curve and application. The languages covered are JavaScript, PERL, PHP, SQL, Python, Ruby, C, C#, and Java. This book is designed to provide a basic working knowledge of each language presented. Case studies show the programming language used in real ways, and resources for exploring each language in more detail are also included.
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Cloud Computing for Science and Engineering

Author: Ian Foster,Dennis B. Gannon

Publisher: MIT Press

ISBN: 0262037246

Category: Computers

Page: 392

View: 5935

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The emergence of powerful, always-on cloud utilities has transformed how consumers interact with information technology, enabling video streaming, intelligent personal assistants, and the sharing of content. Businesses, too, have benefited from the cloud, outsourcing much of their information technology to cloud services. Science, however, has not fully exploited the advantages of the cloud. Could scientific discovery be accelerated if mundane chores were automated and outsourced to the cloud? Leading computer scientists Ian Foster and Dennis Gannon argue that it can, and in this book offer a guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The book surveys the technology that underpins the cloud, new approaches to technical problems enabled by the cloud, and the concepts required to integrate cloud services into scientific work. It covers managing data in the cloud, and how to program these services; computing in the cloud, from deploying single virtual machines or containers to supporting basic interactive science experiments to gathering clusters of machines to do data analytics; using the cloud as a platform for automating analysis procedures, machine learning, and analyzing streaming data; building your own cloud with open source software; and cloud security. The book is accompanied by a website, Cloud4SciEng.org, that provides a variety of supplementary material, including exercises, lecture slides, and other resources helpful to readers and instructors.
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Python for Everybody

Exploring Data in Python 3

Author: Charles R. Severance

Publisher: N.A

ISBN: 9781530051120

Category:

Page: 242

View: 8828

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Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled "Python for Informatics: Exploring Information".There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.pythonlearn.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course.
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Sakai

Free as in Freedom (Alpha) : a Retrospective Diary, Version 0.7.1

Author: Charles R. Severance

Publisher: CreateSpace

ISBN: 9781461166290

Category: Computers

Page: 242

View: 6103

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This book describes the experiences of building the open-source Sakai teaching and learning environment software. Sakai was founded by the University of Michigan, Indiana University, Stanford University, Massachusetts Institute of Technology, the Open Knowledge Initiative(OKI), and the uPortal Project. The Sakai project was funded by the Andrew W. Mellon Foundation, The William and Flora Hewlett Foundation, and over 100 Sakai partner schools and companies for over five million dollars over a two year period. The project was very ambitious with an almost impossible schedule for delivery. Almost nothing in the project went according to the plans and yet today, the Sakai software is in use at nearly 300 schools worldwide with three million daily users and a ten percent market share of research universities. Sakai competes with commercial products like Blackboard and Desire2Learn as well as other open source products like Moodle, OLAT and ATutor. This is the story of the successes and failures and recoveries along the way as well as the fun and stress as the project went forward from an insider's perspective.
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Mastering OpenCV 4 with Python

A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3.7

Author: Alberto Fernández Villán

Publisher: Packt Publishing Ltd

ISBN: 1789349753

Category: Computers

Page: 532

View: 914

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Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key Features Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and Python Apply machine learning and deep learning techniques with TensorFlow, Keras, and PyTorch Discover the modern design patterns you should avoid when developing efficient computer vision applications Book Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learn Handle files and images, and explore various image processing techniques Explore image transformations, including translation, resizing, and cropping Gain insights into building histograms Brush up on contour detection, filtering, and drawing Work with Augmented Reality to build marker-based and markerless applications Work with the main machine learning algorithms in OpenCV Explore the deep learning Python libraries and OpenCV deep learning capabilities Create computer vision and deep learning web applications Who this book is for This book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.
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