Search Results for "learn computer basics" - Page 3
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Showing 231 open source projects for "learn computer basics"
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clavirio
Learn touch typing without leaving the terminal
A free, open-source typing tutor for the terminal. Progressive lessons, practice modes, real-time stats, and a virtual keyboard with finger hints — for QWERTY, Dvorak, and Colemak. Methodology Research on typing skill suggests that skilled typing relies more on implicit procedural control than on explicit knowledge of key locations. The paper also suggests that the keyboard is represented in terms of its row-and-column structure, not as a memorized list of individual... -
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Statistics101 - Resampling Statistics
Use simulation to perform statistical analyses.
Statistics101 is an Integrated Development Environment (IDE) that uses a simple, powerful language called “Resampling Stats” to develop Monte Carlo programs to analyze and solve statistical problems. The original Resampling Stats language and computer program were developed by Dr. Julian Simon (https://www.juliansimon.com/) and Peter Bruce (https://www.scientificamerican.com/author/peter-bruce/) as a new way to teach Statistics to social science students. Of course, social science students aren't the only ones who can benefit. Anyone who wants to learn statistics will find that the resampling approach helps in understanding statistical concepts from the simplest to the most difficult. ... -
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exGENT 64 bit Linux Live System
exGENT Live System is - as the name suggests - based on Gentoo Linux
...INSTALLATION The systems can easily be installed to hard drive and/or a USB flash drive in two ways. Using Calamares Installer or an installation script in /root/install. The installation takes 5 - 20 min. (Depending on computer type). REFRACTA SNAPSHOT When running Build 260626/260602 you can create a different Gentoo/exGENT System. I.e. change everything to your liking and then create a new ISO. Your own! WHO IS exGENT/Gentoo FOR? Experienced Linux users or those who really want to learn Linux. -
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InternVL
A Pioneering Open-Source Alternative to GPT-4o
InternVL is a large-scale multimodal foundation model designed to integrate computer vision and language understanding within a unified architecture. The project focuses on scaling vision models and aligning them with large language models so that they can perform tasks involving both visual and textual information. InternVL is trained on massive collections of image-text data, enabling it to learn representations that capture both visual patterns and semantic meaning. ... -
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operating system simple
Operating System Guide Dari 0
operating_system_guide is a curated, beginner-friendly resource aimed at helping aspiring developers learn how to create an operating system from scratch. Maintained by AzkaDev, the guide collects educational materials, links, and code snippets that walk learners through each major component of OS development—from bootloaders to kernel structures and system calls. While still evolving, the guide acts as a roadmap and inspiration hub for those wanting to explore low-level systems programming... -
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MATLAB Deep Learning Model Hub
Discover pretrained models for deep learning in MATLAB
Discover pre-trained models for deep learning in MATLAB. Pretrained image classification networks have already learned to extract powerful and informative features from natural images. Use them as a starting point to learn a new task using transfer learning. Inputs are RGB images, the output is the predicted label and score. -
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Azure Zero to Hero Course
Repository to learn Azure from Zero
Azure Zero to Hero Course is a comprehensive, day-by-day course repository designed to teach Azure fundamentals and practical skills from the ground up, targeted especially at aspiring DevOps engineers. The README is structured as a multi-day curriculum: early days cover cloud concepts, terminology, and Azure basics such as regions, availability zones, resource groups, and VM creation. Subsequent days dive into networking (VNets, subnets, NSGs, load balancers, firewalls), storage services,... -
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Digital Forensics Guide
Learn all about Digital Forensics and Computer Forensics
The Digital Forensics Guide repository is a comprehensive, structured reference for investigators, analysts, students, and cybersecurity professionals interested in digital forensics principles, tools, methodologies, and workflows. It organizes foundational topics such as evidence acquisition, disk and memory analysis, file system structures, network forensics, artifact extraction, timeline generation, and reporting into digestible modules that help build core competency. Alongside... -
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ParamOS
A Cosmos-based Operating System (Developed for Learning Purpose)
ParamOS is a basic operating system made using Cosmos OS Kit in Visual Studio (C#/.NET). The command line OS has five commands: ‘namaste’ for greetings, ‘about’ to learn more about ParamOS, 'gui' to load the Graphical User Interface (GUI), ‘restart’ to reboot the OS and ‘shutdown’ to shut down the computer. -
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javascript-algorithms
JavaScript implementations of computer science algorithms
javascript-algorithms is a repository that implements a comprehensive collection of classic data structures and algorithmic solutions in JavaScript — including sorting, searching, graph algorithms, dynamic programming, and more. It serves as a learning and reference resource for developers wanting to understand how standard algorithms can be expressed in JavaScript, bridging the gap between theoretical algorithm knowledge and practical implementation usable in web or Node.js contexts.... -
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Complete Machine Learning Package
A comprehensive machine learning repository containing 30+ notebooks
...Each notebook introduces theoretical ideas and then demonstrates how to implement them using Python libraries commonly used in data science, such as NumPy, pandas, scikit-learn, and TensorFlow. The repository also includes examples related to natural language processing, computer vision, and data visualization, giving learners exposure to several subfields of machine learning. By organizing the content into modular notebooks, the project allows users to explore topics independently and experiment with the code directly. -
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bugstack
Java Backend Development Skills Roadbook
...It organizes the learning journey around the real workflow of taking requirements, designing systems, building software, testing quality, and releasing applications. The roadmap covers computer fundamentals, programming foundations, architecture, environment setup, backend development, libraries, debugging, testing, quality analysis, and deployment. It separates core technologies from supporting routes so learners can prioritize what helps them become productive first. The project is useful for students, junior developers, and working programmers who need a clearer view of what to learn next. ... -
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Self-learning-Computer-Science
Resources to learn computer science in your spare time
Self-learning Computer Science is a curated, open-source guide repository designed to help learners independently study computer science topics using high-quality university-level resources. The author (an undergraduate CS student) assembled links to courses from institutions like MIT, UC Berkeley, Stanford, etc., covering mathematics, programming, data structures/algorithms, computer architecture, machine learning, software engineering and more. It’s aimed at learners who find traditional... -
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T81 558
Applications of Deep Neural Networks
...Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This course will introduce the student to classic neural network structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN) and reinforcement learning. Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered. ... -
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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... -
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Reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI
Reinforcement-learning is a widely used educational repository that provides implementations, exercises, and solutions for a broad range of reinforcement learning algorithms, designed to complement foundational texts and courses in the field. The project collects popular approaches such as dynamic programming, Monte Carlo methods, temporal difference learning, Q-learning, SARSA, deep Q-networks, and policy gradient techniques, often demonstrated with Python and OpenAI Gym environments so... -
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Hello AI World
Guide to deploying deep-learning inference networks
Hello AI World is a great way to start using Jetson and experiencing the power of AI. In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train... -
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Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
...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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90DaysOfDevOps
The journey towards a better foundational knowledge of DevOps
...This will not cover all things DevOps but it will cover the areas that I feel will benefit my learning and understanding overall. What is and why do we use DevOps. Learning a Programming Language. Knowing Linux Basics. Understand Networking. Stick to one Cloud Provider. Use Git Effectively. Automate Configuration Management. Learn Infrastructure as Code. And much more! -
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Deep Learning Papers Reading Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn
Deep Learning Papers Reading Roadmap is a widely known curated reading plan for deep learning that helps newcomers and practitioners navigate the vast literature in a structured and intentional way. It is built around several guiding principles: moving from outline to detail, from older foundational papers to state-of-the-art work, and from generic to more specialized areas while keeping a focus on impactful contributions. The roadmap organizes papers into categories such as fundamentals,... -
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Arduino
Open-source electronics platform
Arduino is an open-source physical computing platform based on a simple I/O board and a development environment that implements the Processing/Wiring language. Arduino can be used to develop stand-alone interactive objects or can be connected to software on your computer (e.g. Flash, Processing and MaxMSP). The boards can be assembled by hand or purchased preassembled. Arduino is a popular tool for IoT product development as well as one of the most successful tools for STEM/STEAM education.... -
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Graphics Workshop
Learn computer graphics by writing GPU shaders
Graphics Workshop is an educational computer graphics repository built around writing GPU shaders. It teaches graphics concepts through interactive two-dimensional and three-dimensional browser projects. The workshop covers topics such as fragment shaders, procedural textures, rasterization, lighting, stylized rendering, and real-time ray tracing. It is designed so learners can focus on shader code while the surrounding WebGL and JavaScript harness is already provided. Projects are meant to... -
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Differentiable Neural Computer
A TensorFlow implementation of the Differentiable Neural Computer
...This allows the model to learn how to store and retrieve information across long time horizons, much like a traditional computer. The architecture consists of modular components including an access module for managing memory operations, a controller (often an LSTM or feedforward network) for issuing read/write commands, and submodules for temporal linkage and memory allocation tracking. -
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Deep Learning 500 Questions
500 Questions on Deep Learning using a question-and-answer format
...Edited by Tan Jiyong with contributions from Guo Zizhao, Li Jian, and Dian Songyi, the book systematically covers both theoretical foundations and practical applications of deep learning. The first sections focus on essential mathematics, machine learning basics, and deep learning foundations, establishing the groundwork for more advanced topics. Later chapters explore classic neural network structures such as CNNs, RNNs, and GANs, as well as key applications in computer vision like object detection and image segmentation. The resource also delves into optimization methods, including transfer learning, network architecture design, hyperparameter tuning, model compression, and acceleration techniques. -
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YOLOR
implementation of paper - You Only Learn One Representation
YOLOR is the implementation of “You Only Learn One Representation,” a unified network approach for learning explicit and implicit knowledge together. The project focuses on object detection while exploring how a shared representation can support multiple tasks. It builds on the YOLO family and related PyTorch detection work, combining practical detector training with a research idea about unified representations.
