Open Source Linux Education Software - Page 7
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radlab
Virtual Radiation Detection and Measurement Laboratory Software
Radiation detection and measurement education is necessary for a wide variety of people working with radiation. The equipment and laboratory setup needed for delivering this education are expensive and difficult to assemble due to the large variety of the type of experiments that are desirable to cover. For a basic education one needs to have gamma, beta, alpha and neutron sources, at least one detector to detect each type of radiation and other supplemental instrumentation to perform experiments. Although the radiation exposure due to these radioactive sources in an education laboratory is low, shielding and a private secured place is needed. Nearly two hundred thousand dollars is needed to construct such a basic laboratory described as above. In order to overcome these difficulties, a model of a basic Radiation Detection Laboratory has been created to provide a virtual environment for designing and simulating such experiments. Team: Dagistan Sahin, Muzaffer Sena Sahin, Korcan Kayrin">
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K3DSurf (now MathMod) is a program to visualize and manipulate Mathematical models in three, four, five and six dimensions. K3DSurf supports Parametric equations and Isosurfaces. ****** Welcome to the realm of complex numbers! Change-log for MathMod-11.1 (16/06/2021) 1) Support of graphing functions with complex numbers Z=u+iv in 3D and 4D spaces (demo scripts: "Complex3D_xx" and "Complex4D_Saddle") 2) Added support for HSV (hue, saturation, brightness) coloring model (script: "Complex_Domain_Coloring") 3) Texture definitions (RGB and HSV) for parametric surfaces can now be expressed as functions of complex numbers 4) Added a software implementation for the OpenGL variable gl_FrontFacing (fixed an issue with GPU drivers on MacOSX Catalina). The activation of this patch is available from mathmodconfig.js ("OpenGlConfig"-->"GL_FrontFacingSupport"=false) or the GUI("Appearance"-->"OpenGL Front Surface Support") 5) Bug-fixes, code optimization and documentation update.
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La suite logicielle Monia est destinée à l'apprentissage de l'algorithmique en français. Elle permet de fabriquer un exécutable à partir d'un organigramme, en passant par un programme procédural écrit en pseudo-langage.
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Advanced Trigonometry Calculator
Precision Trigonometry: Advanced Calculator for Complex Math
Advanced Trigonometry Calculator is equipped with a user-friendly interface that allows for easy input of problems and instant computation. Professionals such as engineers who need to perform advanced trigonometric calculations in their work will find this tool extremely useful. More info by clicking below: https://advantrigoncalc.sourceforge.io/ Advanced Trigonometry Calculator was only and always only developed by the Portuguese Renato Alexandre dos Santos Freitas. Also author of poems, reflections and thoughts published on the platform https://www.pensador.com/autor/renato_alexandre_dos_santos_freitas/ ATC is Made in Portugal. He was born in Coimbra on July 6, 1991. He has a degree in Electrical and Telecommunications Engineering and began developing ATC at the beginning of his undergraduate studies. He works for Miclearning, Lda since April 2020. Providing services to Multimac Hito Innovation.">
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GameOver
Training and educating about the web security
About GameOver: Project GameOver was started with the objective of training and educating newbies about the basics of web security and educate them about the common web attacks and help them understand how they work. GameOver has been broken down into two sections. Section 1 consists of special web applications that are designed especially to teach the basics of Web Security. This seciton will cover XSS CSRF RFI & LFI BruteForce Authentication Directory/Path traversal Command execution SQL injection Section 2 is a collection of dileberately insecure Web applications. This section provides a legal platform to test your skills and to try and exploit the vulnerabilities and sharpen your skills before you pentest live sites. We would advice newbies to try and exploit these web applications. These applications provide real life environments and will boost their confidence. -
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xoscope is a digital oscilloscope using input from a sound card or EsounD and/or a ProbeScope/osziFOX and will soon support Bitscope hardware. Includes 8 signal displays, variable time scale, math, memory, measurements, and file save/load.
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AWESOME DATA SCIENCE
Awesome Data Science repository to learn and apply for real world
An open source Data Science repository to learn and apply towards solving real world problems. This is a shortcut path to start studying Data Science. Just follow the steps to answer the questions, "What is Data Science and what should I study to learn Data Science?" Data Science is one of the hottest topics on the Computer and Internet farmland nowadays. People have gathered data from applications and systems until today and now is the time to analyze them. The next steps are producing suggestions from the data and creating predictions about the future. Here you can find the biggest question for Data Science and hundreds of answers from experts. Data scientists combine entrepreneurship with patience, the willingness to build data products incrementally, the ability to explore, and the ability to iterate over a solution. They are inherently interdisciplinary. They can tackle all aspects of a problem, from initial data collection and data conditioning to drawing conclusions. -
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CSS Animation 101
Learn how to bring animation to your web projects
CSS Animation 101 is a tutorial resource that teaches the fundamentals of motion on the web using only CSS. It starts with core building blocks—transitions, transforms, and keyframes—and then layers in timing functions, delays, and choreography to create more expressive sequences. The material stresses clarity and maintainability, showing how to structure styles so animations are easy to reason about and adjust. Throughout, examples demonstrate practical use cases like button feedback, content reveals, loaders, and micro-interactions that enhance user experience without overwhelming it. Performance considerations are discussed, including which properties animate cheaply and how to avoid jank with compositing-friendly transforms. By combining explanation with runnable examples, the resource helps designers and developers develop an intuition for motion that translates directly into everyday interfaces. -
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Catalyst
Accelerated deep learning R&D
Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make something totally new. Catalyst is compatible with Python 3.6+. PyTorch 1.1+, and has been tested on Ubuntu 16.04/18.04/20.04, macOS 10.15, Windows 10 and Windows Subsystem for Linux. It's part of the PyTorch Ecosystem, as well as the Catalyst Ecosystem which includes Alchemy (experiments logging & visualization) and Reaction (convenient deep learning models serving). -
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Containerization (Apple)
Containerization is a Swift package for running Linux containers
This repository provides educational material and sample code that demystify how containerization works and how container components fit together in practice. It walks through the responsibilities of an image format, registry, and runtime, and shows how a minimal runtime can assemble an isolated process with the right filesystem view, environment, and entrypoint. The samples highlight security hardening considerations—such as process isolation, filesystem scoping, and least-privilege execution—so that containers are not just portable, but safer by default. Developers get a blueprint for taking standard container images and running them in a way that respects platform conventions, tooling, and policies. The emphasis is on clarity and standards alignment rather than building a production-grade engine, which makes the code ideal for learning and experimentation. -
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Convolution arithmetic
A technical report on convolution arithmetic in deep learning
A technical report on convolution arithmetic in the context of deep learning. The code and the images of this tutorial are free to use as regulated by the licence and subject to proper attribution. The animations will be output to the gif directory. Individual animation steps will be output in PDF format to the pdf directory and in PNG format to the png directory. We introduce a guide to help deep learning practitioners understand and manipulate convolutional neural network architectures. The guide clarifies the relationship between various properties (input shape, kernel shape, zero padding, strides and output shape) of convolutional, pooling and transposed convolutional layers, as well as the relationship between convolutional and transposed convolutional layers. Relationships are derived for various cases, and are illustrated in order to make them intuitive. -
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Data Science Specialization
Course materials for the Data Science Specialization on Coursera
The Data Science Specialization Courses repository is a collection of materials that support the Johns Hopkins University Data Science Specialization on Coursera. It contains the source code and resources used throughout the specialization’s courses, covering a broad range of data science concepts and techniques. The repository is designed as a shared space for code examples, datasets, and instructional materials, helping learners follow along with lectures and assignments. It spans essential topics such as R programming, data cleaning, exploratory data analysis, statistical inference, regression models, machine learning, and practical data science projects. By providing centralized resources, the repo makes it easier for students to practice concepts and replicate examples from the curriculum. It also offers a structured view of how multiple disciplines—programming, statistics, and applied data analysis—come together in a professional workflow. -
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Dict UK
Project to generate POS tag dictionary for Ukrainian language
A Java-based tool for generating full morphological dictionaries for Ukrainian, applying affix rules to base lexemes to produce all inflected forms with part-of-speech tags—used for natural language processing and spell-checking. -
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Electron Fiddle
The easiest way to get started with Electron
Electron Fiddle lets you create and play with small Electron experiments. It greets you with a quick-start template after opening – change a few things, choose the version of Electron you want to run it with, and play around. Then, save your Fiddle either as a GitHub Gist or to a local folder. Once pushed to GitHub, anyone can quickly try your Fiddle out by just entering it in the address bar. Try Electron without installing any dependencies: Fiddle includes everything you'll need to explore the platform. It also includes examples for every API available in Electron, so if you want to quickly see what a BrowserView is or how the desktopCapturer works, Fiddle has got you covered. Fiddle includes Microsoft's excellent Monaco Editor, the same editor powering Visual Studio Code. It also installs the type definitions for the currently selected version of Electron automatically, ensuring that you always have all Electron APIs only a few keystrokes away. -
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Git-it
Git-it is a (Mac, Win, Linux) desktop app for learning Git and GitHub
Git-it is a desktop (Mac, Windows and Linux) app that teaches you how to use Git and GitHub on the command line. This application contains challenges for learning Git and GitHub, by using real Git and GitHub, not emulators. You'll be learning the awesome (and not so scary) command line and GitHub which means when you finish all of the challenges you'll have real repositories on your GitHub account and green squares on your contribution chart. You will need this app, Git-it as well as a text editor. You'll also of course need Git and the first challenge in Git-it helps you get that set up. But if you want to get a head start, go for it! You'll continue to use Git and your text editor throughout your bright social coding future. We recommend installing GitHub Desktop (free) because it installs Git in the most consistent way across supported operating systems (Windows and Mac). -
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Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing what this book covers in general, I’d describe it as a comprehensive resource on the fundamental concepts of machine learning and deep learning. The first half of the book introduces readers to machine learning using scikit-learn, the defacto approach for working with tabular datasets. Then, the second half of this book focuses on deep learning, including applications to natural language processing and computer vision. -
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Mastering Bitcoin
Mastering Bitcoin 3rd Edition - Programming the Open Blockchain
The bitcoinbook repository contains the source code for Mastering Bitcoin, the authoritative open-source book by Andreas M. Antonopoulos on Bitcoin and cryptocurrency technologies. Written in a collaborative and continuously updated format using Markdown and AsciiDoc, the book serves as a comprehensive technical guide for developers, engineers, and system architects who want to understand how Bitcoin works. It covers the protocol, cryptography, peer-to-peer architecture, wallets, mining, and application development. -
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MathModel
Mathematical Modeling for Graduate Students, Mathematical Modeling
MathModel is a repository dedicated to collecting and organizing resources around mathematical modeling, especially for university students preparing for modeling competitions (e.g. undergraduate and graduate levels). The content spans exemplary competition papers, algorithmic solutions, LaTeX templates, presentation slides, MATLAB tutorials, and mind maps of modeling approaches. It acts as a centralized archive where learners can access high-quality past solutions as references, borrow formatting for their own reports, and study algorithmic strategies that performed well in contests. The repository is structured by topic and resource type so that users can more easily find templates, solved problems, and methodological notes. It also includes auxiliary educational materials like references, recommended textbooks, and guidebooks on mathematical modeling theory. -
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Node.JS Course
Materials, slides and other goodies from my Node.JS courses
This repository accompanies a hands-on Node.js course that builds production-minded skills through projects and exercises rather than slideware. It walks learners from fundamentals to pragmatic topics such as configuration management, process models, database integration, caching, and message queues. Security practices—input validation, secrets handling, and least-privilege IAM—are woven into examples instead of tacked on at the end. The curriculum also covers operational concerns like logging, metrics, health checks, and deployment pipelines so students can ship services with confidence. Code samples are opinionated but accessible, showing how to structure modules, controllers, and tests for clarity and changeability. By the end, participants have a working reference implementation they can adapt for real projects, along with a checklist mindset for production readiness. -
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Octave
my octave exercises for 2011 stanford machine learning class
This repository is a personal archive of Octave exercises and assignments for the 2011 Stanford Machine Learning class. The author uses the Octave programming environment (which is similar to MATLAB) to implement the homework assignments (ex1 through ex7), providing code solutions, cheat sheets, and scratch files. Octave / MATLAB code illustrating algorithms taught in the class. Cheat sheet for Octave / MATLAB commands. Readme and licensing information. Octave / MATLAB code illustrating algorithms taught in the class. -
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Pro Git
Pro Git 2nd Edition
Welcome to the second edition of the Pro Git book. 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. What is “version control”, and why should you care? Version control is a system that records changes to a file or set of files over time so that you can recall specific versions later. For the examples in this book, you will use software source code as the files being version controlled, though in reality you can do this with nearly any type of file on a computer. If you are a graphic or web designer and want to keep every version of an image or layout (which you would most certainly want to), a Version Control System (VCS) is a very wise thing to use. -
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Selfie
An educational software system of a tiny self-compiling C compiler
An educational software system of a tiny self-compiling C compiler, a tiny self-executing RISC-V emulator, and a tiny self-hosting RISC-V hypervisor. Selfie is a project of the Computational Systems Group at the Department of Computer Sciences of the University of Salzburg in Austria. The Selfie Project provides an educational platform for teaching undergraduate and graduate students the design and implementation of programming languages and runtime systems. The focus is on the construction of compilers, libraries, operating systems, and even virtual machine monitors. The common theme is to identify and resolve self-reference in systems code which is seen as the key challenge when teaching systems engineering, hence the name. Selfie is implemented in a single (!) file and kept minimal for simplicity. There is also a simple in-memory linker, a RISC-U disassembler, a garbage collector, L1 instruction and data caches, a profiler, and a debugger with replay. -
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System Design Notebook
Learn System Design step by step
System Design Notebook is a structured, personal knowledge base for learning and practicing system design, written in a way that mirrors real interview and on-the-job thinking. Instead of being a single long article, it’s split into topics like scalability, load balancing, data partitioning, caching, availability, consistency, and communication patterns, so you can study them in isolation. It emphasizes reasoning: why you pick a certain database, why you shard, why you put a queue, and what trade-offs come with each choice. The notes often connect abstract concepts to concrete systems such as social networks, feeds, chat, and file storage, which makes it easier to translate theory into design diagrams. It is meant to be expanded over time, so you can treat it as a living notebook you keep coming back to before interviews or architecture reviews. The repo is especially helpful for people who already know the basics of backend but want to articulate system design decisions clearly. -
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ixy-languages
A high-speed network driver written in C, Rust, C++, Go, C#, Java
ixy-languages is a repository exploring the implementation of the ixy network driver (originally written in C) in multiple programming languages, showing how the same core logic can be expressed across language boundaries. The ixy driver is a minimal DPDK-based user-space NIC driver intended for education, demonstration, and controlled experimentation. This project reimplements the ixy driver architecture in Rust, Go, C++, Zig, and possibly other languages, maintaining the same driver semantics and API so users can compare performance, expressivity, safety, and expressiveness trade-offs. The repository helps systems and networking learners understand how low-level I/O code behaves differently in memory-safe languages versus unsafe ones. Each language subdirectory includes build scripts, language-specific idioms (e.g. unsafe blocks in Rust), binding layers, and benchmarks for packet I/O and latency. -
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Client/server software, human language dictionary databases, and tools supporting the DICT protocol (RFC 2229).
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