Search Results for "ai linux"
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Showing 97 open source projects for "ai linux"
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AI Researcher
An autonomous AI researcher
AI Researcher is an experimental open-source project that demonstrates how multiple AI agents can collaborate to conduct complex research tasks from start to finish with minimal human intervention. It orchestrates agents that can generate research questions, perform literature reviews, execute experiments, analyze results, and synthesize findings into structured outputs like reports or code. Each agent operates with clear roles — such as researcher, analyst, and summarizer — and they... -
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AI Agents for Beginners
12 Lessons to Get Started Building AI Agents
AI Agents for Beginners is a comprehensive educational repository created to introduce developers to the concepts and practical implementation of AI agents. It provides step-by-step lessons that guide users through building autonomous systems capable of reasoning, planning, and interacting with tools. The curriculum combines theory with hands-on exercises, allowing learners to experiment with real agent architectures and workflows. It covers key topics such as prompt design, tool... -
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Maths, CS & AI Compendium
Become a cracked AI/ML Research Engineer
Maths, CS & AI Compendium is an open educational project that explains mathematics, computing, and artificial intelligence from foundational concepts through advanced engineering topics. It favors intuition, practical context, and connected explanations over dense textbook notation. Its chapters cover vectors, matrices, calculus, statistics, probability, machine learning, language processing, computer vision, speech, multimodal learning, robotics, and graph neural networks. It also addresses... -
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Roadmap To Learn Generative AI In 2025
Basic Machine Learning Natural Language Processing Roadmap
Roadmap To Learn Generative AI In 2025 is a curated learning path focused on contemporary generative AI — covering large language models (LLMs), diffusion-based image generation, prompt engineering, multi-modal AI, fine-tuning techniques, and the practical considerations for deploying generative models. It’s aimed at learners and developers who already have some programming or ML basics and wish to specialize in generative AI, offering a modern, structured plan that reflects the state of the... -
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Project NOMAD
Self-contained, offline survival computer with tools, knowledge, & AI
Project N.O.M.A.D. (Node for Offline Media, Archives, and Data) is a self-contained, offline-first knowledge and education server designed to run on local hardware. It combines AI, educational resources, and critical information tools into a single platform accessible through a web browser. Built as a containerized system managed via Docker, it orchestrates multiple applications through a centralized “Command Center” interface. NOMAD enables users to access offline Wikipedia, AI chat, maps,... -
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aie-book
Resources for AI engineers
aie-book is an open-source companion repository that supports a comprehensive guide to building real-world applications with modern AI systems, particularly those based on foundation models. It focuses on bridging the gap between theoretical machine learning knowledge and practical engineering workflows required to deploy AI systems in production. The material emphasizes system design, data pipelines, evaluation strategies, and deployment considerations rather than just model training. It... -
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FDE-Book-of-Forward-Deployed-Engineer
Frontier Deployment Engineer) Beginner's Guide from Scratch
FDE: The Guidance Book of Forward Deployed Engineer is an open Chinese-language book repository about delivering practical value from enterprise AI. It explains the Forward Deployed Engineer role as the bridge between a product’s capabilities and a customer’s real operational needs. The chapters follow a complete delivery journey, from selecting the right problem and winning a customer to deployment, renewal, expansion, and repeatable scaling. The work draws on primary materials, job... -
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Edpuzzle Answers
A Javascript bookmarklet that can get the answers for Edpuzzle
Edpuzzle Answers is a JavaScript-based bookmarklet and script toolkit designed to interact with Edpuzzle assignments by automating video playback and extracting answer data from embedded questions. It operates directly within the browser, requiring no installation beyond saving the bookmarklet, and injects code into the active Edpuzzle page to modify its behavior in real time. The tool can retrieve answers for multiple-choice questions, automate responses, and adjust playback settings,... -
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PageLM
PageLM is a community driven version of NotebookLM
PageLM is an open-source AI-powered education platform that transforms study materials into interactive learning experiences inspired in part by the NotebookLM style of knowledge interaction. It is built to help students, educators, and researchers turn documents and topics into more engaging forms of study rather than leaving content in static notes or isolated files. The platform includes a broad set of learning tools such as contextual chat, Cornell-style note generation, flashcards,... -
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AutoResearchClaw
Autonomous research from idea to paper. Chat an Idea. Get a Paper 🦞
AutoResearchClaw is an open-source framework designed to automatically generate full academic research papers from a single idea or topic. Built in Python, it orchestrates a multi-stage research pipeline that gathers literature, formulates hypotheses, runs experiments, analyzes results, and writes the final paper. The system retrieves real academic references from sources such as arXiv and Semantic Scholar to ensure credible citations. It can automatically generate code for experiments, run... -
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OpenScience
The open-source AI workbench for scientific research
OpenScience is an open-source AI workbench for scientific research. It lets users give an agent a research goal, then have it read literature, form hypotheses, write and run code, run experiments, analyze results, and write up findings. The workspace runs in the browser and includes a file tree, editor, terminal, session history, and scientific rendering for molecules, structures, genomes, and plots. It supports frontier, open-weight, and local models through bring-your-own-key provider... -
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Learn Harness Engineering
Harness engineering official style beginner tutorial
Learn Harness Engineering is an educational repository focused on teaching the principles behind building robust AI agent systems through harness design. It introduces the concept of harness engineering, which involves structuring how agents manage memory, context, and execution rather than relying solely on prompts. The project provides examples, explanations, and patterns for designing reliable, controllable, and scalable agent workflows. It emphasizes modular architecture,... -
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Local Deep Research
95% on SimpleQA (e.g. Qwen3.6-27B on a 3090)
Local Deep Research is an open-source AI-powered research assistant designed to perform deep, iterative investigations by combining large language models with multi-source search capabilities. It runs locally, giving users full control over their data, privacy, and infrastructure while supporting both local and cloud-based LLMs. The system breaks down complex queries into smaller steps, performs parallel searches across web and academic sources, and generates structured, citation-backed... -
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OpenMAIC
Open Multi-Agent Interactive Classroom
OpenMAIC is an open-source multi-agent learning platform built to turn a topic or uploaded material into a fully interactive classroom experience with minimal setup. It is designed around coordinated AI roles, including teacher-like and classmate-like agents that can present information, respond in real time, and participate in live educational dialogue. The platform generates multiple learning scenes rather than a single static output, including slides, quizzes, interactive simulations, and... -
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PocketFlow Tutorial Codebase Knowledge
Codebase to Tutorial
PocketFlow Tutorial Codebase Knowledge is a project that demonstrates how to build an AI agent capable of analyzing arbitrary codebases and generating beginner-friendly tutorials that explain how they work, turning complex source code into clear educational content. The repository builds on a lightweight 100-line LLM framework and uses natural language models to inspect repository structures, identify core abstractions, map dependencies, and articulate the reasoning behind code design and... -
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ML for Trading
Code for machine learning for algorithmic trading, 2nd edition
On over 800 pages, this revised and expanded 2nd edition demonstrates how ML can add value to algorithmic trading through a broad range of applications. Organized in four parts and 24 chapters, it covers the end-to-end workflow from data sourcing and model development to strategy backtesting and evaluation. Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms,... -
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codex-orange-book
A Full-Link Guide to Using Codex from Installation to Real-World Cases
codex-orange-book is an unofficial open-source guide for learning and applying Codex in real software workflows. It is written as a full learning resource rather than a conventional software package. The guide covers installation, configuration, core concepts, standard workflows, practical examples, and extension paths. It explains Codex App, Codex CLI, Codex IDE Extension, Codex Web, cloud workflows, Skills, MCP, Git, GitHub, automation, and memory-related usage. It is aimed at developers,... -
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Book3_Elements-of-Mathematics
From Addition, Subtraction, Multiplication, and Division to ML
Book3_Elements-of-Mathematics is an open learning resource in the Visualize-ML collection that introduces core mathematical foundations required for modern data science and AI. The repository presents topics such as algebra, calculus fundamentals, and mathematical reasoning using a highly visual and beginner-friendly approach. Its goal is to reduce the intimidation barrier often associated with formal mathematics by combining diagrams, structured explanations, and applied examples. The... -
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Open Science
Open Science is an open-source, local-first, model-agnostic research
Open Science is an open-source, local-first AI research workbench built for scientific discovery on macOS, Windows, and Linux. Researchers can describe a task in plain language and let an agent inspect files, execute Python or R, search the web, and call scientific data connectors. The system is model-agnostic, allowing users to connect supported providers, compatible gateways, or subscription-based backends. -
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Book5_Essentials-Probability-Statistics
The book 5 of statistics in simplicity
Book5_Essentials-of-Probability-and-Statistics is a Visualize-ML educational volume that introduces the statistical and probabilistic concepts underpinning modern data analysis and machine learning. The repository explains topics such as distributions, sampling, inference, and uncertainty using visual demonstrations and intuitive narratives. Its teaching philosophy prioritizes conceptual clarity over heavy formalism, making statistical thinking more approachable for beginners. The material... -
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The Grand Complete Data Science Guide
Data Science Guide With Videos And Materials
The Grand Complete Data Science Materials is a repository curated by a data-science educator that aggregates a wide range of learning resources — from basic programming and math foundation to advanced topics in machine learning, deep learning, natural language processing, computer vision, and deployment practices — into a structured, centralized collection aimed at learners seeking a comprehensive path to data science mastery. The repository bundles tutorials, lecture notes, project... -
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TORCS, The Open Racing Car Simulator is a highly portable multi platform car racing simulation. It is used as ordinary car racing game, as AI racing game and as research platform. It runs on Linux (x86, AMD64, ARM and PPC), FreeBSD, OpenSolaris and Windows.
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ktrain
ktrain is a Python library that makes deep learning AI more accessible
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines... -
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Edupro School Management System
All-In-One Modern School Software
Edupro School Management System is an all-in-one, integrated platform designed to streamline school operations and enhance digital learning. Built on powerful open-source technologies—Moodle for Learning Management, Gibbon for Student Information Management, and custom-developed features—it provides a seamless experience for administrators, teachers, students, and parents. With AI-driven learning tools and advanced automation, Edupro School Management System simplifies academic management,... -
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The Ultimate Python Course
Source code and all the details for the Ultimate Python Course
The Ultimate Python Course is a structured learning repository designed to take programmers from Python fundamentals to more advanced concepts. Its chapters cover modules, package management, variables, data types, strings, collections, conditionals, loops, functions, recursion, and file handling. Later sections introduce object-oriented programming, inheritance, polymorphism, type hints, virtual environments, lambda functions, and functional programming tools. Each chapter is accompanied by...