Search Results for "linux educational" - Page 3
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Showing 1324 open source projects for "linux educational"
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Glow OS
System Analysis Software
Glow is an educational, hobbyist operating system written in C and Assembly, developed to help learners understand the internals of OS design and kernel development. Targeting x86_64 systems, Glow features its own kernel, bootloader, and minimal userland. With clear code structure and a simple design, it serves as a playground for experimenting with low-level systems programming, boot sequences, interrupt handling, and basic UI components like shells and text rendering. -
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Hands-On Large Language Models
Official code repo for the O'Reilly Book
Hands-On-Large-Language-Models is the official GitHub code repository accompanying the practical technical book Hands-On Large Language Models authored by Jay Alammar and Maarten Grootendorst, providing a comprehensive collection of example notebooks, code labs, and supporting materials that illustrate the core concepts and real-world applications of large language models. The repository is structured into chapters that align with the educational progression of the book — covering everything... -
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machine-learning-refined
Master the fundamentals of machine learning, deep learning
machine-learning-refined is an educational repository designed to help students and practitioners understand machine learning algorithms through intuitive explanations and interactive examples. The project accompanies a series of textbooks and teaching materials that focus on making machine learning concepts accessible through visual demonstrations and simple code implementations. Instead of presenting algorithms purely through mathematical derivations, the repository emphasizes geometric... -
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DATA SCIENCE ROADMAP
Data Science Roadmap from A to Z
DATA SCIENCE ROADMAP is an educational repository designed to guide learners through the process of becoming proficient in data science and machine learning. The project presents a structured roadmap that outlines the knowledge and skills required for different stages of a data science career. Topics typically include programming with Python, statistics, mathematics, machine learning algorithms, data visualization, and big data technologies. The roadmap also includes links to courses,... -
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RAG from Scratch
Demystify RAG by building it from scratch
RAG From Scratch is an educational open-source project designed to teach developers how retrieval-augmented generation systems work by building them step by step. Instead of relying on complex frameworks or cloud services, the repository demonstrates the entire RAG pipeline using transparent and minimal implementations. The project walks through key concepts such as generating embeddings, building vector databases, retrieving relevant documents, and integrating the retrieved context into... -
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LLMs-Zero-to-Hero
From nobody to big model (LLM) hero
LLMs-Zero-to-Hero is an open-source educational project designed to guide learners through the complete process of understanding and building large language models from the ground up. The repository presents a structured learning pathway that begins with fundamental concepts in machine learning and progresses toward advanced topics such as model pre-training, fine-tuning, and deployment. Rather than relying entirely on existing frameworks, the project encourages readers to implement... -
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aosabook
The Architecture of Open Source Applications
aosabook is the source repository for The Architecture of Open Source Applications, a book series about how real open-source systems are designed and built. The project collects the written material, source files, and build assets used to publish the books. Its purpose is educational, showing developers how experienced engineers solve complex design problems in actual software projects. The material is aimed at junior developers who want to learn architectural thinking, as well as more... -
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AI Coding Dictionary
AI coding jargon, explained in plain English
Dictionary of AI Coding is an educational reference project that explains AI coding terminology in plain English. It is designed for developers who use coding agents but feel slowed down by unclear vocabulary, hidden assumptions, confusing billing concepts, and inconsistent model behavior. The dictionary organizes terms across models, context windows, tools, environments, failure modes, handoffs, and related AI coding workflows. Its tone is intentionally direct and accessible, avoiding dense... -
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xqvm-py
A python implementation of the Quip Network's quantum virtual machine
xq-py is a Python implementation of the Quip Network’s quantum virtual machine, offering a more accessible and flexible alternative to the Rust-based version for experimentation and rapid development. It is designed to provide similar functionality to xq-rs while prioritizing ease of use, readability, and integration with Python-based data science and research tools. The project enables developers to simulate or prototype quantum-inspired computations without needing to work at a lower... -
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Machine Learning Study
This repository is for helping those interested in machine learning
Machine Learning Study is an educational repository containing tutorials and study materials related to machine learning and data science using Python. The project compiles notebooks, explanatory documents, and practical code examples that illustrate common machine learning workflows. Topics covered include supervised learning algorithms, feature engineering, model training, and performance evaluation techniques. The repository is structured as a learning resource that guides readers through... -
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Book4_Power-of-Matrix
Book_4_Matrix Power | The Iris Book: From Addition, Subtraction
Book4_Power-of-Matrix is an open educational repository that forms part of the Visualize-ML book series, focusing on explaining matrix mathematics and linear algebra concepts through visual and intuitive methods. The project is designed to help readers progress from basic arithmetic toward machine learning fundamentals by building a strong conceptual understanding of vectors, matrices, and their operations. It combines explanatory text, diagrams, and Python examples to bridge theory and... -
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go-algorithms
Algorithms and data structures for golang
go-algorithms is an open-source educational repository that provides implementations of common algorithms and data structures written in the Go programming language. The project is designed primarily as a learning resource to help developers understand how fundamental computer science concepts can be implemented idiomatically in Go. It includes a wide range of classic sorting, searching, and numerical algorithms alongside basic collection structures such as stacks, queues, linked lists, and... -
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handy-ollama
Implement CPU from scratch and play with large model deployments
handy-ollama is an open-source educational project designed to help developers and AI enthusiasts learn how to deploy and run large language models locally using the Ollama platform. The repository serves as a structured tutorial that explains how to install, configure, and use Ollama to run modern language models on personal hardware without requiring advanced infrastructure. A key focus of the project is enabling users to run large models even without GPUs by leveraging optimized CPU-based... -
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Train LLM From Scratch
A straightforward method for training your LLM
Train LLM From Scratch is an educational PyTorch project that shows how to build and train a transformer-based language model from the ground up. It is based on the architecture described in Attention Is All You Need and is designed to make the training pipeline understandable rather than hidden behind a large framework. The repository walks through the process from downloading data to generating text with a trained model. It supports training smaller or larger models, including million- and... -
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Transformers & LLMs cheatsheet
VIP cheatsheet for Stanford's CME 295 Transformers and Large Language
Transformers & LLMs cheatsheet is an educational repository focused on transformers, large language models, and modern generative AI architectures based on Stanford CME 295 coursework. The project compiles structured notes, mathematical explanations, diagrams, and implementation references covering transformer internals, attention mechanisms, tokenization, training pipelines, and inference strategies. It is designed to help students and practitioners understand the technical foundations... -
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LLM From Scratch
Build and train a GPT-style language model
LLM From Scratch is a hands-on educational workshop project that teaches developers how to build and train a GPT-style language model entirely from scratch using PyTorch. Instead of relying on high-level abstractions or prebuilt frameworks, the project walks users through implementing every core component manually, including tokenization, transformer architecture, training loops, and autoregressive text generation. The repository is intentionally simplified to focus on conceptual clarity,... -
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ffmprovisr
Repository of useful FFmpeg commands for archivists
ffmprovisr is an educational web-based resource designed to help users understand and construct FFmpeg commands through a curated collection of practical recipes. It organizes common multimedia tasks into categorized examples, allowing users to quickly find solutions for operations such as transcoding, trimming, filtering, and metadata handling. Each recipe includes a sample command along with a detailed explanation of its components, helping users learn how FFmpeg flags and parameters work.... -
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Machine Learning Tutorials Repository
Dive deep into the realms of Machine Learning and other topics
The Machine Learning Tutorials Repository is a comprehensive collection of resources, examples, and implementations designed to help users understand and apply machine learning concepts. It covers a wide range of topics, including supervised learning, unsupervised learning, neural networks, and data preprocessing techniques. The project is structured to provide both theoretical explanations and practical code examples, making it suitable for learners at different levels. It includes... -
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sectorlisp
Bootstrapping LISP in a Boot Sector
The sectorlisp project is a minimal implementation of the Lisp programming language designed to fit within extremely constrained environments. It is engineered to run in very small memory footprints, making it suitable for educational purposes and experimentation with low-level programming concepts. The project demonstrates how a functional programming language can be implemented with minimal resources while still retaining core features. It focuses on simplicity, providing a stripped-down... -
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dive-into-llms
"Dive into LLMs" series of practical programming tutorials
The dive-into-llms project is an educational resource designed to provide a comprehensive introduction to large language models and their underlying concepts. It combines theoretical explanations with practical examples, guiding users through topics such as model architecture, training processes, and inference techniques. The repository is structured as a learning pathway, making it accessible to both beginners and intermediate practitioners interested in understanding how LLMs work. It... -
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Gameboy
Full featured Cross-platform GameBoy emulator by Rust
Mohanson GameBoy is a minimalist Game Boy emulator project focused on clarity, experimentation, and educational value rather than full compatibility or performance optimization. It is designed as a clean implementation of the Game Boy architecture, typically written in a high-level language such as Python or Rust depending on the version, making it approachable for developers studying emulator design. The project emphasizes core components such as CPU instruction decoding, memory management,... -
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AlphaTree
DNN && GAN && NLP && BIG DATA
AlphaTree is an educational repository that provides a visual roadmap of deep learning models and related artificial intelligence technologies. The project focuses on explaining the historical development and relationships between major neural network architectures used in modern machine learning. It presents diagrams and documentation describing the evolution of models such as LeNet, AlexNet, VGG, ResNet, DenseNet, and Inception networks. The repository organizes these architectures into a... -
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thorough-pytorch
PyTorch Getting Started Tutorial, read online
thorough-pytorch is an educational project designed to teach deep learning using the PyTorch framework through a structured learning series. The repository provides tutorials and practical exercises that guide learners from fundamental PyTorch concepts to more advanced deep learning techniques. It emphasizes a learning approach that combines theoretical explanations with hands-on coding exercises so that students can build and experiment with neural networks directly. The project encourages... -
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machine_learning_examples
A collection of machine learning examples and tutorials
machine_learning_examples is an open-source repository that provides a large collection of machine learning tutorials and practical code examples. The project aims to teach machine learning concepts through hands-on programming rather than purely theoretical explanations. It includes implementations of many machine learning algorithms and neural network architectures using Python and popular libraries such as TensorFlow and NumPy. The repository covers a wide range of topics including... -
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ML Retreat
Machine Learning Journal for Intermediate to Advanced Topics
ML Retreat is an open-source learning repository that serves as a structured journal documenting advanced topics in machine learning and artificial intelligence. The project compiles detailed notes, technical explanations, and curated resources that guide readers through complex concepts across modern AI research. Rather than functioning as a traditional tutorial series, the repository is organized as a learning journey that progressively explores increasingly advanced subjects. Topics...
