This is the textbook of a graduate course given in 2024 at the University of Twente on "Scientific computing with open-source software".
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.
Spec is the default UI framework for Pharo. To build UI’s in Spec existing widgets or even complete UI’s are reused and configured to form a new UI.
This book first shows the basics of Spec and how it enables reuse of UIs. It then treats UI layout in detail before moving on to explaining the management of windows. Some of the more advanced widgets are also discussed as well as the dynamic features of Spec. Lastly, the book also contains a chapter with tips and tricks.
Squeak is a modern open-source development environment for the classic Smalltalk-80 programming language. Despite being the first purely object-oriented language and environment, Smalltalk is in many ways still far ahead of its successors in promoting a vision of an environment where everything is an object, and anything can change at run-time.
Help! I’m completely new to coding and I need to learn R and RStudio! What do I do?
If you’re asking yourself this question, then you’ve come to the right place! Start with the “Introduction for students” section.
Are you an instructor hoping to use this book in your courses? We recommend reading the “Introduction for students” section first. Then, read the “Introduction for instructors” section for more information on how to teach with this book.
Are you looking to connect with and contribute to ModernDive? Then, read the “Connect and contribute” section for information on how.
Are you curious about the publishing of this book? Then, read the “About this book” section for more information on the open-source technology, in particular R Markdown and the bookdown package.
This record and link is to the website for the book: Statistical Inference via Data Science: A ModernDive into R and the Tidyverse!
The goal of this text is to provide a practical introduction to systems integration by designing and implementing an actual system. Readers are taken through a project that builds a containerized web application using Docker and then expands it to use the Kubernetes orchestration framework. Through the practical examples topics such as version control, interchange formats, front end design, messaging frameworks, container-based virtualization, and container orchestration are covered.
El nivel académico que pretende abordar el libro es en las diferentes licenciaturas e ingenierías que consideren tópicos en el área de interacción humano computadora, así como los posgrados relacionados con la temática. El libro describe diferentes tipos de interacción que pueden ofrecer las aplicaciones interactivas donde a través de la interfaz gráfica es posible guiar y hacer fácil la tarea del usuario. Así pues, el lector puede encontrar diferentes trabajos que especifican desde los requerimientos del usuario hasta el diseño, programación y evaluación de distintas aplicaciones interactivas.
Chapter about cognitive styles and the Cognitive Style Heuristics (from the GenderMag Project). From "Handbook of Software Engineering": https://www.oercommons.org/courses/handbook-of-software-engineering-methods
A textbook chapter on evaluating software. Includes video demonstration of a GenderMag Walkthrough.
The book is appropriately comprehensive, covering the basics as well as interesting and important applications of Bayesian methods.
This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science. This book focuses on discrete models, which include graphs, cellular automata, and agent-based models. They are often characterized by structure, rules and transitions rather than by equations. They tend to be more abstract than continuous models; in some cases there is no direct correspondence between the model and a physical system.
The examples and supporting code for this book are in Python. You should know core Python and you should be familiar with object-oriented features, at least using objects if not defining your own. If you are not already familiar with Python, you might want to start with my other book, Think Python, which is an introduction to Python for people who have never programmed, or Mark Lutz’s Learning Python, which might be better for people with programming experience.
Data structures and algorithms are among the most important inventions of the last 50 years, and they are fundamental tools software engineers need to know. But in my opinion, most of the books on these topics are too theoretical, too big, and too bottom-up:
*Too theoretical: Mathematical analysis of algorithms is based on simplifying assumptions that limit its usefulness in practice. Many presentations of this topic gloss over the simplifications and focus on the math. In this book I present the most practical subset of this material and eliminate the rest.
*Too big: Most books on these topics are at least 500 pages, and some are more than 1000. By focusing on the topics I think are most useful for software engineers, I kept this book under 250 pages.
*Too bottom-up: Many data structures books focus on how data structures work (the implementations), with less about how to use them (the interfaces). In this book, I go “top down”, starting with the interfaces. Readers learn to use the structures in the Java Collections Framework before getting into the details of how they work.
Finally, many present this material out of context and without motivation: it’s just one damn data structure after another!
I try to alleviate the boredom by organizing the topics around an application—web search—that uses data structures extensively, and is an interesting and important topic in its own right.
This application also motivates some topics that are not usually covered in an introductory data structures class, including persistent data structures, with Redis, and streaming algorithms.
I have made difficult decisions about what to leave out, but I have made some compromises. I include a few topics that most readers will never use, but that they might be expected to know, possibly in a technical interview. For these topics, I present both the conventional wisdom as well as my reasons to be skeptical.
This book also presents basic aspects of software engineering practice, including version control and unit testing. Each chapter ends with an exercise that allows readers to apply what they have learned. Each exercise includes automated tests that check the solution. And for most exercises, I present my solution at the beginning of the next chapter.
This book is intended for college students in computer science and related fields, as well as professional software engineers, people training in software engineering, and people preparing for technical interviews.
I assume that the reader knows Java at an intermediate level, but I explain some Java features along the way, and provide pointers to supplementary material.
People who have read Think Java or Head First Java are prepared for this book.
Think Java is an introduction to Java programming for beginners. It is tailored for students preparing for the Computer Science Advanced Placement (AP) Exam, but it is for anyone who wants to learn Java.
Think OS is an introduction to Operating Systems for programmers. In many computer science programs, Operating Systems is an advanced topic. By the time students take it, they usually know how to program in C, and they have probably taken a class in Computer Architecture. Usually the goal of the class is to expose students to the design and implementation of operating systems, with the implied assumption that some of them will do research in this area, or write part of an OS.
Think Stats is an introduction to Probability and Statistics for Python programmers.
*Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets.
*If you have basic skills in Python, you can use them to learn concepts in probability and statistics. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding.
This text is a practical guide for linguists, and programmers, who work with data in multilingual computational environments. We introduce the basic concepts needed to understand how writing systems and character encodings function, and how they work together at the intersection between the Unicode Standard and the International Phonetic Alphabet. Although these standards are often met with frustration by users, they nevertheless provide language researchers and programmers with a consistent computational architecture needed to process, publish and analyze lexical data from the world's languages. Thus we bring to light common, but not always transparent, pitfalls which researchers face when working with Unicode and IPA. Having identified and overcome these pitfalls involved in making writing systems and character encodings syntactically and semantically interoperable (to the extent that they can be), we created a suite of open-source Python and R tools to work with languages using orthography profiles that describe author- or document-specific orthographic conventions. In this cookbook we describe a formal specification of orthography profiles and provide recipes using open source tools to show how users can segment text, analyze it, identify errors, and to transform it into different written forms for comparative linguistics research.
The Washington State Department of Licensing contracted with the University of Washington to create an educational resource to provide an introduction to data stewardship principles. The course breaks down key concepts to familiarize individuals that are new to data stewardship and for those that wish to learn to think of data as an asset.
Scientific research and design is traditionally made to be published in books or magazines by use of text and images. The arrival of digital media and internet changed this dramatically and allowed new possibilities and far better accessibility of this work. Be this as it may, it is still paramount that the accuracy and completeness of published scientific work is maintained. This course will focus on this integrated concept, the learning of how to successfully make and publish your own website. In 6 lectures the several aspects of traditional scientific research will be treated by using the contemporary media. The course has the following study goals, that correspond with the given assignments and lectures: publishing own study and design work; making your work retrievable for others by use of key words; making use of digital media to describe own work; describing and evaluating of own work; making a bibliography and iconography; intrepretenting an image as a scientific document;describing in key words; compare images scientifically; deducting design types from image comparison; deducting design concepts from image comparison; deducting design models from image comparison; deducting design programs from image comparison; integrating different design concepts and becoming acquainted with research methods; defining an object of research, problem field, target field, design tools, own competence and context of research; formulating a site, context factors, motivation, design program, contribution, intended results and planning; justifying, referring and concluding of own work; giving and receiving professional critique.
Web Accessibility for Developers is a technical book aimed primarily at programmers. Learn how to develop accessible interactivity on the Web and gain expertise using WAI-ARIA, a W3C specification that enables optimal use of assistive technologies, like screen readers, when navigating the Web.