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Handbook of Software Engineering Methods
Lara Letaw · Oregon State University · 2024
Software engineering can help people create sustainable, extensible programs that solve problems people care about.I won’t tell you how to be a software engineer; you’ll learn that over time by doing it. Instead, this book is about software engineering methods: Ways people achieve specific objectives in software engineering—that can save your project. My hope is that, after reading this book (or parts of it), you’ll feel better equipped for software engineering.
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An Open Guide to Data Structures and Algorithms
Paul Bible; Lucas Moser; Mia Scarlato · PALNI · 2023
This textbook serves as a gentle introduction for undergraduates to theoretical concepts in data structures and algorithms in computer science while providing coverage of practical implementation (coding) issues. The field of computer science (CS) supports a multitude of essential technologies in science, engineering, and communication as a social medium. The varied and interconnected nature of computer technology permeates countless career paths making CS a popular and growing major program. Mastery of the science behind computer science relies on an understanding of the theory of algorithms and data structures. These concepts underlie the fundamental tradeoffs that dictate performance in terms of speed, memory usage, and programming complexity that separate novice programmers from professional practitioners.
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The Shallow and the Deep: A biased introduction to neural networks and old school machine learning
Michael Biehl · University of Groningen Press · 2023
The Shallow and the Deep is a collection of lecture notes that offers an accessible introduction to neural networks and machine learning in general. However, it was clear from the beginning that these notes would not be able to cover this rapidly changing and growing field in its entirety. The focus lies on classical machine learning techniques, with a bias towards classification and regression. Other learning paradigms and many recent developments in, for instance, Deep Learning are not addressed or only briefly touched upon. Biehl argues that having a solid knowledge of the foundations of the field is essential, especially for anyone who wants to explore the world of machine learning with an ambition that goes beyond the application of some software package to some data set. Therefore, The Shallow and the Deep places emphasis on fundamental concepts and theoretical background. This also involves delving into the history and pre-history of neural networks, where the foundations for most of the recent developments were laid. These notes aim to demystify machine learning and neural networks without losing the appreciation for their impressive power and versatility.
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Artificial Intelligence and Librarianship
Martin Frické · SoftOption · 2024
Courses on Artificial Intelligence (AI) and Librarianship in ALA-accredited Masters of Library and Information (MLIS) degrees are rare. We have all been surprised by ChatGPT and similar Large Language Models. Generative AI is an important new area for librarianship. It is also developing so rapidly that no one can really keep up. Those trying to produce AI courses for the MLIS degree need all the help they can get. This book is a gesture of support. It consists of about 100,000 words on the topic, with a 4-500 item bibliography. The third edition has changes and additions. These include: a new Chapter 6 on evaluation and the future new materials in Chapter 5 on current large language and multimodal models scattered revisions, corrections, and updates.
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Prealgebra via Python Programming: First Steps to Perform Large Scale Computational Tasks in the Sciences and Engineerings
Sergio Rojas · Sergio Rojas · 2018
This book was written for students and instructors who want to learn how to use a computer for other than the most common uses, such as web browsing, document creation, or paying bills online. This book is for anyone who wants to perform computational tasks that they design. In other words, if you wish to learn how to program a computer, this book is for you. Because prealgebra is a subject that practically everyone is supposed to learn in grade school, it provides a platform to introduce basic computer programming concepts. Consequently, this book should also be of interest to students in middle or high school who want to learn how to program, and who are willing to invest the time and effort in learning a programming language that they could continue using throughout their schooling and in their professional life. Similarly, this book could also be of interest to pre-service and in-service mathematics teachers wishing to have at their disposal a complementary tool to assist in fostering understanding, competency, and interest in mathematics among their students. This book can be integrated with the teachers’ curriculum as way to tackle non-traditional math problems using an inexpensive modern computer language. By the end of the book, a reader will have learned enough to be able to write a preliminary, step-by-step one variable equation solver that can be expanded in the future to use with more complex equations. In other words, by the end of the book, you will be able to write code that programs their machines to solve equations. This code is foundational and readers are ecouraged to learn on their own how to build on it to suit their mathematics learning needs.
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Producing Open Source Software: How to Run a Successful Free Software Project
Karl Fogel · Karl Fogel · 2005
Producing Open Source Software is a book about the human side of open source development. It describes how successful projects operate, the expectations of users and developers, and the culture of free software. The book is released under an open copyright. You can buy it in bookstores, order copies from O'Reilly Media, or browse and download it here.
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Programming Persistent Memory: A Comprehensive Guide for Developers
Stteve Scargall · Apress · 2020
Beginning and experienced programmers will use this comprehensive guide to persistent memory programming. You will understand how persistent memory brings together several new software/hardware requirements, and offers great promise for better performance and faster application startup times—a huge leap forward in byte-addressable capacity compared with current DRAM offerings. This revolutionary new technology gives applications significant performance and capacity improvements over existing technologies. It requires a new way of thinking and developing, which makes this highly disruptive to the IT/computing industry. The full spectrum of industry sectors that will benefit from this technology include, but are not limited to, in-memory and traditional databases, AI, analytics, HPC, virtualization, and big data. Programming Persistent Memory describes the technology and why it is exciting the industry. It covers the operating system and hardware requirements as well as how to create development environments using emulated or real persistent memory hardware. The book explains fundamental concepts; provides an introduction to persistent memory programming APIs for C, C++, JavaScript, and other languages; discusses RMDA with persistent memory; reviews security features; and presents many examples. Source code and examples that you can run on your own systems are included. What You’ll Learn Understand what persistent memory is, what it does, and the value it brings to the industry Become familiar with the operating system and hardware requirements to use persistent memory Know the fundamentals of persistent memory programming: why it is different from current programming methods, and what developers need to keep in mind when programming for persistence Look at persistent memory application development by example using the Persistent Memory Development Kit (PMDK) Design and optimize data structures for persistent memory Study how real-world applications are modified to le
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Pro Git: Everything You Need to Know About Git (English)
Scott Chacon; Ben Straub · Apress · 2022
The entire Pro Git book, written by Scott Chacon and Ben Straub and published by Apress, is available here. All content is licensed under the Creative Commons Attribution Non Commercial Share Alike 3.0 license. Print versions of the book are available on Amazon.com. The version found here has been updated with corrections and additions from hundreds of contributors. If you see an error or have a suggestion, patches and issues are welcome in its GitHub repository.
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Computer Systems Security: Planning for Success
Ryan Tolboom · Ryan Tolboom
The text, labs, and review questions in this book are designed as an introduction to the applied topic of computer security. With these resources students will learn ways of preventing, identifying, understanding, and recovering from attacks against computer systems. This text also presents the evolution of computer security, the main threats, attacks and mechanisms, applied computer operation and security protocols, main data transmission and storage protection methods, cryptography, network systems availability, recovery, and business continuation procedures.
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Earth, Space, and Environmental Science Explorations with ArcGIS Pro
Wing Cheung · Wing Cheung
When I first started teaching Geographic Information Systems (GIS) over 15 years ago, there were only a handful of GIS tutorial books on the market. While a few of them focused on a particular theme, many of them were mainly technical publications with no unifying theme. These publications are perfect for teaching new users about basic GIS operations and continue to be invaluable to many users today. However, these publications consisted of tutorials focusing on vastly different real-world scenarios, and felt a little disjointed to integrate into a class that focuses on a specific field (e.g. Environmental Science, Geography, Urban Planning). Since then, I am happy to see that there has been a proliferation of publications that are not only focused on introducing the technology, but also provide an introduction to a specific field as well as GIS. It is with this consideration in mind that I wrote this book to not only introduce students to the tools in ArcGIS Pro, but also to provide a glimpse into some of the topics that may be covered in an introductory course in Geography, Environmental Science, or related disciplines. I aimed to achieve a balance of technical instruction and information about Earth, Space, and Environmental Sciences, to make this publication helpful for new GIS learners, as well as students who may be interested in learning about the applications of GIS in the Earth, Space, and Environmental Sciences. Before you begin with the book, please download and unzip the data for the book at https://tinyurl.com/ESESGIS. Each chapter will begin with a list of the technical objectives for the lab exercise, which is particularly useful to refer to should you need a refresher on how to perform a particular task at a later date. The list of technical objectives is followed by a short introduction that provides the context for the exercise. Subsequently, you will find the step-by-step directions for the exercises with questions embedded throughout (in yellow h
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Making Sense of Digital Humanities
Julian Chambliss; Ellen Moll · Michigan State University · 2022
Taking up the challenge of navigating the complex world of digital humanities, Making Sense of Digital Humanities offers readers an exploration of the many ways scholars have employed the diverse toolkit of digital humanities to create a better understanding of the synergies and disruptions created by technological change. Rooted in a concern for the daunting tasks associated with teaching and learning about the digital humanities, this volume hopes to provide easy entry into a complex topic while highlighting how an understanding of digital humanities can transform our thinking about technology in the modern world.
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Game Based and Adaptive Learning Strategies
Carrie Miller; Odbayar Batsaikhan; Elizabeth Pluskwik · Minnesota State Colleges and Universities · 2022
This book is designed to accompany a graduate-level instructional design course: Game-Based and Adaptive Learning, but could also be used for undergraduate teacher education or instructional design courses. The original texts and material for this book came from the development of a course for Brandeis University as part of their MS in Learner Experience Design program. This material can be used to teach pre-service teachers, in-service teachers, and instructional designers about game-based and adaptive learning. Assessments used in the actual Game-based and Adaptive Learning course are included in the final chapter and serve as recommendations for assessments of the learning outcomes. The material in this book pairs well with Using Game-Based Learning Online – A Cookbook of Recipes by The EGG. The Faculty Showcase materials were developed by dedicated faculty during the course of a year-long game development workshop in which faculty were introduced to GBL, developed game prototypes, played a variety of games, and finally playtested their designs. The work they continue to do in the area of GBL is part of the inspiration for this book. If you would like to contribute your own case study, please contact me at carrie.miller@mnsu.edu for consideration. Carrie Lewis Miller, Ph.D.- editor/author- Instructional Designer, Minnesota State University, Mankato
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Mathematical Modeling and Simulation with MATLAB
Sheldon Lee; Megan Buzby · University of Alaska Southeast · 2021
This textbook attempts to provide you with an overview of the commonly used basic mathematical models, as well as a wide range of applications. It offers a perspective that brings you back to the modeling process and the assumptions that go into it.
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Patterns for Beginning Programmers
David Bernstein · James Madison University · 2022
Programming patterns are solutions to problems that require the creation of a small fragment of code that will be part of a larger program. Hence, this book is about teaching you how to write such fragments of code. However, it is not about teaching you the syntax of the statements in the fragments, it assumes that you already know the syntax. Instead, it is about finding solutions to problems that arise when first learning to program.
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Building Information - Representation and Management: Principles and Foundations for the Digital Era
Alexander Koutamanis · TU Delft Open · 2022
The book presents a coherent theory of building information, focusing on its representation and management in the digital era. It addresses issues such as the information explosion and the structure of analogue building representations to propose a parsimonious approach to the deployment and utilization of symbolic digital technologies like BIM. It also considers the matching representation of AECO processes in terms of tasks, so as to connect to information processing and support both information management and decision taking.
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Evidence-based Software Engineering
Derek Jones · Knowledge Software · 2020
This book discusses what is currently known about software engineering, based on an analysis of all the publicly available data. This aim is not as ambitious as it sounds, because there is not a great deal of data publicly available. The intent is to provide material that is useful to professional developers working in industry; until recently researchers in software engineering have been more interested in vanity work, promoted by ego and bluster. The material is organized in two parts, the first covering software engineering and the second the statistics likely to be needed for the analysis of software engineering data.
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Deleting Dystopia: Re-Asserting Human Priorities in the Age of Surveillance Capitalism
Richard Slaughter · University of Southern Queensland · 2021
Deleting Dystopia confirms that the existential threats posted by the misuse of advanced digital technologies are real. But, in place of apathy and fatalism, Slaughter explores ways of understanding the threat, conceptualising solutions and identifying strategies that lead away from digital authoritarian futures towards those funded on humanly viable values and practices.
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Introduction to Statistical Thinking
Benjamin Yakir · Benjamin Yakir · 2010
The target audience for this book is college students who are required to learn statistics, students with little background in mathematics and often no motivation to learn more. It is assumed that the students do have basic skills in using computers and have access to one. Moreover, it is assumed that the students are willing to actively follow the discussion in the text, to practice, and more importantly, to think. Teaching statistics is a challenge. Teaching it to students who are required to learn the subject as part of their curriculum, is an art mastered by few. In the past I have tried to master this art and failed. In desperation, I wrote this book. This book uses the basic structure of generic introduction to statistics course. However, in some ways I have chosen to diverge from the traditional approach. One divergence is the introduction of R as part of the learning process. Many have used statistical packages or spreadsheets as tools for teaching statistics. Others have used R in advanced courses. I am not aware of attempts to use R in introductory level courses. Indeed, mastering R requires much investment of time and energy that may be distracting and counterproductive for learning more fundamental issues. Yet, I believe that if one restricts the application of R to a limited number of commands, the benefits that R provides outweigh the difficulties that R engenders. Another departure from the standard approach is the treatment of probability as part of the course. In this book I do not attempt to teach probability as a subject matter, but only specific elements of it which I feel are essential for understanding statistics. Hence, Kolmogorov’s Axioms are out as well as attempts to prove basic theorems and a Balls and Urns type of discussion. On the other hand, emphasis is given to the notion of a random variable and, in that context, the sample space.
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Inventory Analytics
Roberto Rossi · Roberto Rossi · 2021
Inventory Analytics provides a comprehensive and accessible introduction to the theory and practice of inventory control – a significant research area central to supply chain planning. The book outlines the foundations of inventory systems and surveys prescriptive analytics models for deterministic inventory control. It further discusses predictive analytics techniques for demand forecasting in inventory control and also examines prescriptive analytics models for stochastic inventory control. Inventory Analytics is the first book of its kind to adopt a practicable, Python-driven approach to illustrating theories and concepts via computational examples, with each model covered in the book accompanied by its Python code. Originating as a collection of self-contained lectures, Inventory Analytics will be an indispensable resource for practitioners, researchers, teachers, and students alike.
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Defend Dissent
Glencora Borradaile · Oregon State University · 2021
Defend Dissent is an introduction to cryptography paired with the social impacts of surveillance and the protective potential of encryption, with a focus on US social movements. Each chapter ends with a story that brings social context to the material—from surveillance used against contemporary US protests to the African National Congress’s use of partially manual encryption in fighting apartheid in South Africa in the 80s.This book can be read linearly, or you can pick and choose what you would like to learn about. Each chapter is prefaced with what you should read first (for background) and concludes with what you might want to read next.