Showing 4819 open source projects for "learning"

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  • 1
    Google Cloud Platform Go Samples

    Google Cloud Platform Go Samples

    Sample apps and code written for Google Cloud

    Google Cloud Platform Go Samples repository is a comprehensive collection of Go-based code examples that demonstrate how to build applications and services using Google Cloud Platform. It provides developers with practical implementations that cover a wide spectrum of cloud functionalities, including storage, compute, networking, and machine learning services. Each sample is designed to be easily reusable, allowing developers to copy code directly into their own projects as a starting point for development. The repository includes both simple quickstart examples and more advanced application patterns, often accompanied by documentation guides that explain how to deploy and run them in different environments. ...
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  • 2
    MyScaleDB

    MyScaleDB

    A @ClickHouse fork that supports high-performance vector search

    MyScaleDB is an open-source SQL vector database designed for building large-scale AI and machine learning applications that require both analytical queries and semantic vector search. The system is built on top of the ClickHouse database engine and extends it with specialized indexing and search capabilities optimized for vector embeddings. This design allows developers to store structured data, unstructured text, and high-dimensional vector embeddings within a single database platform. ...
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  • 3
    Generative AI for beginners with JS

    Generative AI for beginners with JS

    Join a time-traveling adventure where you meet history’s legends

    Generative AI with JavaScript is an educational repository created by Microsoft that teaches developers how to build applications powered by large language models using the JavaScript ecosystem. The project is structured as a multi-lesson curriculum that introduces the concepts, tools, and practical techniques required to create generative AI applications. Each lesson includes written explanations, hands-on exercises, quizzes, and supporting videos to help developers learn the material...
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  • 4
    RAG from Scratch

    RAG from Scratch

    Demystify RAG by building it from scratch

    ...Each example is written with detailed explanations so that developers can understand the internal mechanics of semantic search and context-aware language generation. The repository emphasizes learning through direct implementation, allowing users to see how each component of the RAG architecture functions independently.
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  • 5
    Claude Code Skills & Plugins Hub

    Claude Code Skills & Plugins Hub

    270+ Claude Code plugins with 739 agent skills

    Claude Code Plugins Plus Skills is a large open-source ecosystem of plugins and AI “skills” designed to extend the capabilities of Claude Code development agents. The repository functions as a marketplace-style collection of hundreds of plugins and specialized skills that enable Claude Code to perform complex development, automation, and operational tasks. These plugins cover a wide range of domains including DevOps automation, security testing, API debugging, infrastructure management, and...
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  • 6
    Pixeltable

    Pixeltable

    Data Infrastructure providing an approach to multimodal AI workloads

    Pixeltable is an open-source Python data infrastructure framework designed to support the development of multimodal AI applications. The system provides a declarative interface for managing the entire lifecycle of AI data pipelines, including storage, transformation, indexing, retrieval, and orchestration of datasets. Unlike traditional architectures that require multiple tools such as databases, vector stores, and workflow orchestrators, Pixeltable unifies these functions within a...
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  • 7
    trench

    trench

    Open-Source Analytics Infrastructure

    ...By combining streaming ingestion with fast analytical queries, the system supports use cases such as product analytics dashboards, observability pipelines, and machine learning data preparation.
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  • 8
    AI Powered Knowledge Graph Generator

    AI Powered Knowledge Graph Generator

    AI Powered Knowledge Graph Generator

    AI-Powered Knowledge Graph is an open-source project focused on building knowledge graph systems that integrate artificial intelligence and machine learning to represent complex relationships between data entities. Knowledge graphs organize information as networks of nodes and relationships, allowing applications to analyze connections between concepts, datasets, or real-world entities. By incorporating AI techniques such as natural language processing and semantic reasoning, the project enables systems to automatically extract relationships and insights from large volumes of data. ...
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  • 9
    The LLM Evaluation guidebook

    The LLM Evaluation guidebook

    Sharing both practical insights and theoretical knowledge about LLM

    The Evaluation Guidebook is an open educational resource created by Hugging Face that explains how to evaluate machine learning and large language models effectively. It compiles practical insights and theoretical knowledge gathered from real-world evaluation work, including experience managing the Open LLM Leaderboard and designing evaluation tools. The guidebook teaches developers how to design evaluation pipelines, select appropriate metrics, and interpret model performance results. ...
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  • 10
    Cradle framework

    Cradle framework

    The Cradle framework is a first attempt at General Computer Control

    Cradle is an open-source framework designed to enable AI agents to perform complex computer tasks by interacting with software environments in a way similar to human users. The system introduces the concept of General Computer Control, where AI agents receive screenshots as input and perform actions through simulated keyboard and mouse operations. This approach allows agents to interact with any software interface without relying on specialized APIs or predefined automation scripts. The...
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  • 11
    HuixiangDou

    HuixiangDou

    Overcoming Group Chat Scenarios with LLM-based Technical Assistance

    ...The assistant uses retrieval and ranking methods along with language model reasoning to produce accurate answers for technical topics such as computer vision and machine learning projects. It can be integrated into messaging platforms such as WeChat or other team collaboration tools to assist developer communities.
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  • 12
    MatMul-Free LM

    MatMul-Free LM

    Implementation for MatMul-free LM

    ...These optimizations can significantly reduce memory consumption and potentially improve computational efficiency during both training and inference. The repository provides implementations of models at several parameter scales and includes tools for experimenting with the architecture using modern machine learning frameworks.
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  • 13
    ai-cookbook

    ai-cookbook

    Examples and tutorials to help developers build AI systems

    ai-cookbook is an open-source repository that provides practical tutorials, code examples, and reusable snippets designed to help developers build real-world artificial intelligence applications quickly. The project focuses on delivering hands-on engineering guidance rather than theoretical explanations, allowing developers to copy, adapt, and integrate working code directly into their own systems. The repository contains examples that demonstrate how to build AI workflows using modern tools...
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  • 14
    CineCLI

    CineCLI

    CineCLI is a cross-platform command-line movie browser

    ...It connects to popular online movie databases to fetch metadata such as titles, release dates, ratings, genres, casts, posters, and plot summaries, presenting all of that in a concise, text-friendly format suitable for terminals or scripts. Users can search by keyword, year, or exact title and then drill into detailed views for individual films, making it useful for creating watchlists, learning more about films before watching, or integrating movie lookup into shell workflows. CineCLI also supports paginated results and filters so users can navigate large search outputs without overwhelming their screens. Because it runs entirely from the command line, it’s ideal for developers, movie enthusiasts in headless environments, or anyone who prefers text-based tools over web browsers.
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  • 15
    RSC Explorer

    RSC Explorer

    A tool for people curious about the React Server Components protocol

    RSC Explorer is an educational, experiment-friendly tool for understanding the React Server Components (RSC) protocol by making the streaming process visible and inspectable. It runs both the “server” and “client” sides of RSC in the browser, removing the need to set up a full backend just to learn how the protocol behaves. The core experience is the ability to step through the RSC stream incrementally, seeing what data arrives at each moment and how that data maps to the React tree being...
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  • 16
    AI Agents Masterclass

    AI Agents Masterclass

    Follow along with my AI Agents Masterclass videos

    AI Agents Masterclass is an educational open-source repository designed to teach developers how to build, train, and deploy intelligent AI agents using modern tooling and workflow patterns. The project includes structured lessons, code examples, and practical exercises that cover foundational concepts like prompt engineering, chaining agents, tool usage, plan execution, evaluation, and safety considerations. It breaks down how autonomous agents interact with external systems, handle...
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  • 17
    Step3-VL-10B

    Step3-VL-10B

    Multimodal model achieving SOTA performance

    Step3-VL-10B is an open-source multimodal foundation model developed by StepFun AI that pushes the boundaries of what compact models can achieve by combining visual and language understanding in a single architecture. Despite having only about 10 billion parameters, it delivers performance that rivals or even surpasses much larger models (10×–20× larger) on a wide range of multimodal benchmarks covering reasoning, perception, and complex tasks, positioning it as one of the most powerful...
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  • 18
    Chinese-XLNet

    Chinese-XLNet

    Chinese XLNet pre-trained model

    ...This model is trained on large-scale Chinese text datasets to learn linguistic patterns, long-range dependencies, and semantic nuance typical of Chinese writing, making it useful for tasks like text classification, question answering, named entity recognition, and language generation. Chinese-XLNet offers an alternative to models like BERT by emphasizing autoregressive and permutation-based learning, which can lead to performance improvements on certain benchmarks and tasks.
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  • 19
    JSCamp InfoJobs

    JSCamp InfoJobs

    Content and exercises fromJSCamp InfoJobs

    JSCamp InfoJobs is the companion repository for JSCamp InfoJobs, an intensive full-stack JavaScript bootcamp in Spanish designed to take students from fundamentals to advanced topics. It is organized into numbered modules like 00-html-css, 01-javascript, 02-react, 03-router-and-zustand, 04-node, 05-typescript, 06-inteligencia-artificial, 07-sql, 08-ci-cd, and 09-docker, mirroring the curriculum of the bootcamp.The README explains that students will build a complete project step by step...
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  • 20
    Preguntas de entrevista para React

    Preguntas de entrevista para React

    Questions about React for job interviews

    Preguntas de entrevista para React is a comprehensive Spanish-language resource containing typical React interview questions organized from beginner to expert level. The repository is not just a list of questions: it includes detailed explanations in Spanish, making it useful as both an interview prep guide and a deeper learning reference.The content is structured in sections (beginner, intermediate, expert), covering everything from “What is React?” and JSX basics to advanced topics such as hydration, server components, useTransition, useSyncExternalStore, server actions, streaming rendering APIs, and new React 19 features. It also includes JavaScript fundamentals that are essential for React, like array methods, optional chaining, arrow functions, and module syntax, so learners can strengthen their base while studying React itself.
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  • 21
    vue2-elm

    vue2-elm

    Large single page application with 45 pages built on vue2 + vuex

    ...It places strong emphasis on responsive UI, transitions, and user feedback patterns that feel app-like on mobile devices. Developers can study API consumption patterns and mock data handling to simulate real production constraints. As a learning resource, it gives a practical playground for debugging, performance considerations, and code readability in a real-world scale example
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  • 22
    Vision Transformer Pytorch

    Vision Transformer Pytorch

    Implementation of Vision Transformer, a simple way to achieve SOTA

    ...Because it stays close to vanilla PyTorch, you can integrate custom datasets and training loops without framework lock-in. It’s widely used as an educational reference for people learning transformers in vision and as a lightweight baseline for research prototypes. The project encourages experimentation—swap optimizers, change augmentations, or plug the transformer backbone into downstream tasks.
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  • 23
    nanochat

    nanochat

    The best ChatGPT that $100 can buy

    ...The repository stitches together every stage of the lifecycle: tokenizer training, pretraining a Transformer on a large web corpus, mid-training on dialogue and multiple-choice tasks, supervised fine-tuning, optional reinforcement learning for alignment, and finally efficient inference with caching. Its north star is approachability and speed: you can boot a fresh GPU box and drive the whole pipeline via a single script, producing a usable chat model in hours and a clear markdown report of what happened. The code is written to be read—concise training loops, transparent configs, and minimal wrappers—so you can audit each step, tweak it, and rerun without getting lost in framework indirection.
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  • 24
    Tunix

    Tunix

    A JAX-native LLM Post-Training Library

    Tunix is a JAX-native library for post-training large language models, bringing supervised fine-tuning, reinforcement learning–based alignment, and knowledge distillation into one coherent toolkit. It embraces JAX’s strengths—functional programming, jit compilation, and effortless multi-device execution—so experiments scale from a single GPU to pods of TPUs with minimal code changes. The library is organized around modular pipelines for data loading, rollout, optimization, and evaluation, letting practitioners swap components without rewriting the whole stack. ...
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  • 25
    Penzai

    Penzai

    A JAX research toolkit to build, edit, & visualize neural networks

    Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained inspection and modification after training. Its modular design includes tools for tree manipulation, named axes, and declarative neural network construction. ...
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