Python For Informatics

Author: Charles Severance
Publisher: CreateSpace
ISBN: 9781492339243
Size: 35.92 MB
Format: PDF
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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.

The Librarian S Introduction To Programming Languages

Author: Beth Thomsett-Scott
Publisher: Rowman & Littlefield
ISBN: 1442263342
Size: 49.30 MB
Format: PDF, Docs
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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.

Big Data And Social Science

Author: Ian Foster
Publisher: CRC Press
ISBN: 1498751431
Size: 24.51 MB
Format: PDF, Docs
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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.

Cloud Computing For Science And Engineering

Author: Ian Foster
Publisher: MIT Press
ISBN: 0262037246
Size: 60.87 MB
Format: PDF, Docs
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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.

Python For Everybody

Author: Charles R. Severance
Publisher:
ISBN: 9781530051120
Size: 40.65 MB
Format: PDF
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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.

Sakai

Author: Charles R. Severance
Publisher: CreateSpace
ISBN: 9781461166290
Size: 68.26 MB
Format: PDF, Kindle
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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.

Mastering Opencv 4 With Python

Author: Alberto Fernández Villán
Publisher: Packt Publishing Ltd
ISBN: 1789349753
Size: 13.66 MB
Format: PDF
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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.

Practical Data Analysis

Author: Hector Cuesta
Publisher: Packt Publishing Ltd
ISBN: 1785286668
Size: 35.85 MB
Format: PDF
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A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.

Building Bioinformatics Solutions

Author: Conrad Bessant
Publisher: OUP Oxford
ISBN: 0191643203
Size: 18.59 MB
Format: PDF, ePub, Docs
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Bioinformatics encompasses a broad and ever-changing range of activities involved with the management and analysis of data from molecular biology experiments. Despite the diversity of activities and applications, the basic methodology and core tools needed to tackle bioinformatics problems is common to many projects. This unique book provides an invaluable introduction to three of the main tools used in the development of bioinformatics software - Perl, R and MySQL - and explains how these can be used together to tackle the complex data-driven challenges that typify modern biology. These industry standard open source tools form the core of many bioinformatics projects, both in academia and industry. The methodologies introduced are platform independent, and all the examples that feature have been tested on Windows, Linux and Mac OS. Building Bioinformatics Solutions is suitable for graduate students and researchers in the life sciences who wish to automate analyses or create their own databases and web-based tools. No prior knowledge of software development is assumed. Having worked through the book, the reader should have the necessary core skills to develop computational solutions for their specific research programmes. The book will also help the reader overcome the inertia associated with penetrating this field, and provide them with the confidence and understanding required to go on to develop more advanced bioinformatics skills.