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Artificial Intelligence & ML · Awesome GitHub Repositories

150 repos

Awesome GitHub RepositoriesArtificial Intelligence & ML

This category encompasses all aspects of artificial intelligence, machine learning, deep learning, and related agentic systems and models.

Explore 150 awesome GitHub repositories matching artificial intelligence & ml · Artificial Intelligence & ML. Refine with filters or upvote what's useful.

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Awesome Artificial Intelligence & ML GitHub Repositories

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  • Anduin2017/HowToCook

    Anduin2017/HowToCook

    98,028GitHubView on GitHub↗

    HowToCook is a structured culinary knowledge base and computational engine designed for the management and scaling of instructional cooking content. It provides a framework for organizing technical preparation procedures and ingredient data, allowing users to maintain consistent culinary standards across various meal s

    Dockerfilechinesecookbookcooking
  • mtdvio/every-programmer-should-know

    mtdvio/every-programmer-should-know

    97,839GitHubView on GitHub↗

    This project is a comprehensive, community-curated knowledge base designed to support software engineers in mastering both fundamental computer science principles and practical industry methodologies. It serves as a centralized reference library that aggregates technical resources, academic literature, and professional

    cc-bycollectioncomputer-science
  • ant-design/ant-design

    ant-design/ant-design

    97,624GitHubView on GitHub↗

    Ant Design is an enterprise-grade component library and design system framework built for developing complex, data-heavy web applications. It provides a comprehensive collection of pre-built, state-driven interface elements that map data properties to rendered components, ensuring consistent interaction patterns and vi

    TypeScriptant-designantddesign-systems
  • pytorch/pytorch

    pytorch/pytorch

    97,601GitHubView on GitHub↗

    PyTorch is a machine learning framework centered on a GPU-ready tensor library that supports multi-dimensional array operations across both CPU and accelerator hardware. It provides a foundational infrastructure for mathematical computation and dynamic neural network construction, utilizing a tape-based automatic diffe

    Pythonautograddeep-learninggpu
  • Shubhamsaboo/awesome-llm-apps

    Shubhamsaboo/awesome-llm-apps

    96,116GitHubView on GitHub↗

    This repository serves as a comprehensive collection of resources, templates, and starter code for building artificial intelligence applications. It provides a centralized hub for developers to access practical implementations of common workflows, including retrieval-augmented generation pipelines and autonomous agent

    Pythonagentsllmspython
  • nvbn/thefuck

    nvbn/thefuck

    95,503GitHubView on GitHub↗

    This tool is a rule-based engine designed to automate the correction of failed terminal commands. By integrating directly into the shell environment, it intercepts command execution errors, analyzes exit codes and output streams, and applies corrective logic to resolve typos or syntax mistakes. It functions as a persis

    Pythonpythonshell
  • ggml-org/llama.cpp

    ggml-org/llama.cpp

    95,400GitHubView on GitHub↗

    Llama.cpp is an inference engine designed for the local execution of text-based and multimodal language models on consumer hardware. It provides a core environment for running models that process both text and image inputs, utilizing hardware-accelerated backends to optimize performance across diverse CPU and GPU archi

    C++ggml
  • fastapi/fastapi

    fastapi/fastapi

    95,356GitHubView on GitHub↗

    FastAPI is a web framework for building APIs with Python. It leverages standard language type hints to provide automatic data validation, request parsing, and interactive API documentation generation. The framework supports asynchronous request handling and manages execution contexts to prevent blocking the main event

    Pythonapiasyncasyncio
  • google-gemini/gemini-cli

    google-gemini/gemini-cli

    94,954GitHubView on GitHub↗

    This project provides a command-line interface for managing autonomous agent workflows, task orchestration, and system-level automation. It includes a comprehensive framework for defining agent skills, managing persistent memory, and delegating tasks to specialized subagents. Users can configure complex planning modes,

    TypeScriptaiai-agentscli
  • openai/whisper

    openai/whisper

    94,839GitHubView on GitHub↗

    This project is a speech recognition and translation engine that utilizes a sequence-to-sequence transformer architecture to convert audio into text. It is built upon a weakly supervised learning framework, which leverages large-scale, unlabelled audio-transcript data to create generalized speech representations capabl

    Python
  • tailwindlabs/tailwindcss

    tailwindlabs/tailwindcss

    93,668GitHubView on GitHub↗

    Utility-first CSS framework for fast, design-system-friendly styling.

    TypeScriptcssframeworkutility
  • immich-app/immich

    immich-app/immich

    92,953GitHubView on GitHub↗

    Immich is a self-hosted media management platform designed to provide a centralized, private repository for photos and videos. It functions as a comprehensive system for organizing, backing up, and viewing personal media collections across mobile devices, web browsers, and external storage locations. By maintaining ful

    TypeScriptbackup-toolfluttergoogle-photos
  • florinpop17/app-ideas

    florinpop17/app-ideas

    90,567GitHubView on GitHub↗

    App-ideas is a development platform that integrates autonomous AI agents into local environments to orchestrate code review, automated fix application, and workflow management. It functions as a command-line interface that connects external AI assistants to your codebase, enabling iterative development cycles through p

    applicationscodingcodingchallenges
  • gin-gonic/gin

    gin-gonic/gin

    88,134GitHubView on GitHub↗

    Gin is a web framework designed for building high-performance web services and APIs. It functions as a middleware-oriented engine that processes incoming HTTP requests through a sequential chain of handlers, allowing for the modular management of cross-cutting concerns such as authentication and logging. The framework

    Goframeworkgingo
  • ChatGPTNextWeb/NextChat

    ChatGPTNextWeb/NextChat

    87,317GitHubView on GitHub↗

    NextChat is a self-hosted web application that provides a unified interface for interacting with multiple large language models. It functions as a conversational platform where users can manage and switch between diverse AI providers through configurable API backends, maintaining full control over their data and infras

    TypeScriptcalclaudechatgptclaude
  • microsoft/markitdown

    microsoft/markitdown

    87,305GitHubView on GitHub↗

    This project is an AI-powered document processing engine designed to transform diverse file formats into structured Markdown. By leveraging multimodal language models, it performs complex layout analysis and semantic text extraction, allowing for the conversion of both unstructured files and scanned images into machine

    Pythonautogenautogen-extensionlangchain
  • opencv/opencv

    opencv/opencv

    86,238GitHubView on GitHub↗

    OpenCV is a comprehensive computer vision library designed for real-time performance and cross-platform deployment. It provides a native execution environment that leverages multi-threaded operations and automated memory management to handle intensive computational tasks, including image processing and machine learning

    C++c-plus-pluscomputer-visiondeep-learning
  • rasbt/LLMs-from-scratch

    rasbt/LLMs-from-scratch

    85,529GitHubView on GitHub↗

    This repository serves as an educational framework for building large language models from the ground up. It provides a structured curriculum that guides learners through the end-to-end lifecycle of model development, including data processing, architecture design, and optimization. By focusing on low-level implementat

    Jupyter Notebookaiartificial-intelligencechatbot
  • home-assistant/core

    home-assistant/core

    84,936GitHubView on GitHub↗

    Home Assistant is a centralized home automation platform designed to orchestrate diverse internet-connected devices and services. It functions as a local-first control system that normalizes heterogeneous hardware protocols into a unified set of entities, attributes, and services. The core architecture relies on an eve

    Pythonasynciohacktoberfesthome-automation
  • firecrawl/firecrawl

    firecrawl/firecrawl

    84,034GitHubView on GitHub↗

    Firecrawl is a web data extraction platform designed to convert unstructured web content into clean, LLM-ready formats like markdown or JSON. It functions as an autonomous web crawler and scraper, capable of mapping entire domains, performing recursive navigation, and executing complex data gathering tasks. By leveragi

    TypeScriptaiai-agentsai-crawler
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Browse tags

  • AI Agent Development Guides1 sub-tagInstructional resources and best practices for designing, building, and refining the behavior of AI agents.
  • AI Code Generation1 sub-tagSoftware utilities that leverage machine learning models to automatically write, refactor, or document source code.
  • AI Development Guides4 sub-tagsEducational materials and technical documentation covering standard practices for developing and maintaining artificial intelligence applications.
  • AI Domains1 sub-tagSpecialized sectors and industry-specific applications where artificial intelligence technologies are deployed and integrated.
  • AI Ecosystems1 sub-tagIntegrated environments and platforms that support the development and distribution of third-party AI extensions and plugins.
  • AI Gateways1 sub-tagMiddleware layers that sit between applications and AI models to manage security, filtering, and content moderation.
  • AI Model Constraints1 sub-tagMechanisms and configurations that restrict or modify how AI models process inputs and generate outputs.
  • AI Orchestration5 sub-tagsSystems that coordinate complex AI tasks, manage data context, and sequence multiple model interactions.
  • AI Orchestration Frameworks1 sub-tagSoftware libraries and frameworks designed to build and manage automated pipelines for AI model execution.
  • AI Persona Simulations1 sub-tagSimulated environments that allow AI agents to interact with specific interfaces like command-line terminals.
  • AI Personas8 sub-tagsPredefined AI configurations designed to mimic specific roles, professional expertise, or interactive communication styles.
  • AI Security and Governance4 sub-tagsFrameworks and research focused on the safety, security, and ethical governance of artificial intelligence systems.
  • AI Use Cases1 sub-tagPractical scenarios and workflows demonstrating how artificial intelligence can be applied to solve specific business problems.
  • Agent Lifecycle Management1 sub-tagTools and processes for managing the operational lifecycle, deployment, and loading of autonomous software agents.
  • Agentic Systems Frameworks9 sub-tagsDevelopment environments, orchestration frameworks, and infrastructure specifically designed for building and managing autonomous agentic workflows.
  • Artificial Intelligence39 sub-tagsBroad technologies and methodologies used to create, deploy, and interact with intelligent, autonomous software systems.
  • Artificial Intelligence & Machine Learning121 sub-tagsComprehensive tools, frameworks, and methodologies for the end-to-end development and research of machine learning applications.
  • Artificial Intelligence Architectures7 sub-tagsStructural patterns and design methodologies for building complex, agent-based, and context-aware artificial intelligence systems.
  • Artificial Intelligence Assistants1 sub-tagSpecialized AI tools designed to assist users with specific tasks like mathematical formula generation and calculation.
  • Artificial Intelligence Capabilities5 sub-tagsAdvanced functional abilities of AI models, particularly those involving visual perception, reasoning, and multimodal data processing.
  • Artificial Intelligence Challenges1 sub-tagCommon technical and operational hurdles encountered during the design and implementation of AI agents.
  • Artificial Intelligence Concepts2 sub-tagsFundamental theories and core principles underlying the operation of autonomous agents and intelligent systems.
  • Artificial Intelligence Configuration1 sub-tagTools and settings for managing the configuration, behavior, and system-level instructions of AI models.
  • Artificial Intelligence Development4 sub-tagsMethodologies and technical practices for engineering prompts, managing context, and structuring outputs in AI development.
  • Artificial Intelligence Engines1 sub-tagCore processing engines that integrate external data retrieval with generative models to improve response accuracy.
  • Artificial Intelligence Integration6 sub-tagsLayers, clients, and frameworks for integrating AI services into applications.
  • Artificial Intelligence Interfaces2 sub-tagsUser-facing interfaces that provide natural language or unified access to various artificial intelligence services.
  • Artificial Intelligence Learning Resources1 sub-tagEducational resources focused on the design, architecture, and implementation of intelligent agent systems.
  • Artificial Intelligence Models5 sub-tagsVarious categories of machine learning models specialized for tasks like text generation, media creation, and code analysis.
  • Artificial Intelligence Orchestration3 sub-tagsSystems that manage the interaction between multiple models or agents to optimize task execution and routing.
  • Artificial Intelligence Patterns2 sub-tagsStandardized architectural patterns for routing requests and integrating large language models into software applications.
  • Artificial Intelligence Platforms2 sub-tagsSoftware platforms that provide environments for document analysis and local orchestration of language models.
  • Artificial Intelligence Quality Assurance1 sub-tagTesting and validation frameworks designed to ensure the reliability and accuracy of multi-agent AI systems.
  • Artificial Intelligence Reasoning1 sub-tagAlgorithms and methodologies designed to enable machines to perform logical deduction and strategic planning tasks.
  • Artificial Intelligence Research10 sub-tagsAcademic and technical studies focused on advancing the capabilities, efficiency, and evaluation of large language models.
  • Artificial Intelligence Resources6 sub-tagsEducational materials, guides, and reference data intended to assist developers in implementing artificial intelligence technologies.
  • Artificial Intelligence Runtimes1 sub-tagExecution environments optimized for loading, hosting, and running large language models in production or development.
  • Artificial Intelligence Services4 sub-tagsManaged cloud-based interfaces and APIs that provide access to specialized artificial intelligence capabilities and model inference.
  • Artificial Intelligence Systems1 sub-tagIntegrated software architectures that combine external data retrieval with generative models to produce context-aware outputs.
  • Artificial Intelligence Tooling6 sub-tagsSoftware utilities and development environments that facilitate the building, monitoring, and management of artificial intelligence applications.
  • Artificial Intelligence Workflows3 sub-tagsStructured processes and automation toolkits designed to streamline the development and execution of artificial intelligence tasks.
  • Autonomous Driving Models1 sub-tagComputational models specifically trained to navigate vehicles and make real-time driving decisions in complex environments.
  • Autonomous Systems1 sub-tagFrameworks and software components that enable systems to perform complex tasks without continuous human intervention.
  • Business Intelligence Agents1 sub-tagAutomated agents configured to gather, analyze, and synthesize market data for business decision-making support.
  • Chat Completion Interfaces1 sub-tagUser interfaces and API wrappers that facilitate interactive, multi-turn text communication with artificial intelligence models.
  • Computer Vision Systems14 sub-tagsSpecialized tools and frameworks for processing visual data, including object tracking, face analysis, and image segmentation.
  • Conversational AI1 sub-tagSystems and resources for building, deploying, and operating agents capable of natural language interaction and structured dialogue.
  • Conversational AI Frameworks1 sub-tagSoftware libraries and architectural patterns used to structure and deploy conversational agent logic.
  • Deep Learning1 sub-tagResources and frameworks for developing, training, and implementing neural networks and machine intelligence models.
  • Deep Learning Frameworks10 sub-tagsProgramming libraries and APIs that provide the foundational building blocks for defining and training neural networks.
  • Developer Tools5 sub-tagsSoftware utilities and command-line tools that assist developers in writing, managing, and debugging codebases.
  • Development Agents1 sub-tagAutomated software agents capable of performing end-to-end programming tasks and managing development lifecycles.
  • Document Analysis5 sub-tagsAlgorithms and systems designed to extract, interpret, and digitize information from structured and unstructured documents.
  • Document Analysis Tools2 sub-tagsSpecialized utilities for parsing document layouts and verifying the accuracy of extracted data.
  • Domain Specific Models1 sub-tagMachine learning models fine-tuned to perform specialized tasks within specific industry or data domains.
  • Driver Assistance Systems2 sub-tagsSoftware systems that monitor vehicle surroundings and provide automated assistance to improve driver safety.
  • Feature Extraction1 sub-tagTechniques and tools for transforming raw data into numerical representations suitable for machine learning models.
  • Function Calling1 sub-tagMechanisms that allow language models to trigger external software functions or APIs based on user input.
  • Generative AI Resources9 sub-tagsCollections of tools, libraries, and guides for creating and managing generative artificial intelligence content.
  • Identity Processing1 sub-tagAlgorithms that identify and group facial features to recognize or verify individual identities.
  • Language Detection1 sub-tagTools that analyze text samples to determine the underlying language using heuristic or statistical methods.
  • Language Model Orchestration12 sub-tagsSystems and frameworks that coordinate complex interactions between language models, external tools, and data sources.
  • Language Models4 sub-tagsComputational models trained to understand, generate, and manipulate human language across various tasks.
  • Machine Learning18 sub-tagsTools, algorithms, and resources for developing, training, and deploying predictive models and data-driven applications.
  • Machine Learning Architectures16 sub-tagsStructural designs and mathematical patterns used to define the internal connectivity and data flow of neural networks.
  • Machine Learning Capabilities1 sub-tagMethods for grouping unlabeled data points based on inherent similarities or patterns within a dataset.
  • Machine Learning Domains2 sub-tagsSpecialized areas of application focusing on specific deployment environments or model adaptation techniques.
  • Machine Learning Engines1 sub-tagCore software components that provide unified interfaces for executing models across diverse hardware and software backends.
  • Machine Learning Frameworks18 sub-tagsSoftware libraries and environments providing the foundational tools to construct, train, and execute machine learning models.
  • Machine Learning Infrastructure15 sub-tagsFoundational systems and hardware-level tools required to support the development, deployment, and scaling of machine learning workflows.
  • Machine Learning Models8 sub-tagsPre-trained or configurable mathematical representations designed to perform specific predictive or generative tasks.
  • Machine Learning Pipelines11 sub-tagsAutomated sequences of operations that manage the end-to-end flow of data from ingestion through model training and deployment.
  • Machine Learning Research9 sub-tagsExperimental techniques and novel methodologies currently being explored to advance the state of machine learning capabilities.
  • Machine Learning Tasks4 sub-tagsSpecific problem types that machine learning models are designed to solve through predictive or analytical processing.
  • Machine Learning Tooling13 sub-tagsSoftware utilities and interfaces that assist developers in preparing data, managing models, and evaluating performance metrics.
  • Machine Learning Utilities6 sub-tagsHelper functions and auxiliary tools used to process data, generate embeddings, or manage model weights.
  • Model Abstractions1 sub-tagProgramming interfaces that decouple model logic from specific service providers or underlying implementation details.
  • Model Configuration Tools1 sub-tagUtilities for defining and managing the parameters and settings required to initialize or process model inputs.
  • Model Context Protocol Integrations1 sub-tagStandardized configurations for connecting local or remote services to the Model Context Protocol ecosystem.
  • Model Context Protocols4 sub-tagsStandardized protocols and interfaces enabling AI agents to communicate with and utilize external tools and data sources.
  • Model Distribution Formats1 sub-tagStandardized file structures and serialization methods used to package and distribute trained model weights.
  • Model Execution2 sub-tagsEnvironments and configuration settings required to load and run models for inference tasks.
  • Model Execution Interfaces1 sub-tagStandardized programming interfaces that provide a consistent way to interact with various model execution backends.
  • Model Input Configurations1 sub-tagSettings and preprocessing methods used to format diverse data types for consumption by machine learning models.
  • Model Integration2 sub-tagsTools and client libraries that facilitate the connection of applications to external or multi-provider model services.
  • Model Lifecycle Management12 sub-tagsSystems and processes for managing the entire operational lifecycle of a model from initial training to final deployment.
  • Model Resources1 sub-tagRepositories and directories that organize and provide access to collections of pre-trained machine learning models.
  • Multimodal AI2 sub-tagsSystems capable of processing and interpreting information across multiple data modalities, such as text and images.
  • Multimodal Processing3 sub-tagsTechniques and models designed to handle, synchronize, and analyze data streams from multiple distinct sources.
  • Natural Language Processing15 sub-tagsLibraries and techniques for analyzing, processing, and extracting insights from human language data.
  • Neural Network Architectures14 sub-tagsStructural frameworks and modular components used to design, configure, and organize neural network layers and data flow.
  • Neuromorphic Computing1 sub-tagHardware and software architectures inspired by biological neural systems to achieve energy-efficient computation.
  • Object-Oriented APIs1 sub-tagProgramming interfaces that allow developers to define neural network components using object-oriented design patterns.
  • Optimization Strategies1 sub-tagAlgorithms and strategies used to dynamically adjust training parameters to improve model convergence and performance.
  • Pretrained ModelsReady-to-use machine learning models trained on large datasets for specific tasks like image recognition or natural language processing.
  • Prompt Engineering Tools15 sub-tagsUtilities and frameworks designed to help users craft, refine, and manage inputs for large language models.
  • Reinforcement Learning1 sub-tagMethods and environments for training models to perform complex tasks through reward-based learning and iterative optimization.
  • Reinforcement Learning Optimizations1 sub-tagTechniques and tools focused on improving the efficiency, speed, and memory usage of reinforcement learning training processes.
  • Research Automation2 sub-tagsSystems that automate the collection, analysis, and synthesis of information to accelerate scientific or market research workflows.
  • Research Papers2 sub-tagsAcademic and technical documents detailing advancements, methodologies, and experimental results in the field of machine learning.
  • Research Topics1 sub-tagSpecific areas of inquiry and emerging challenges currently being explored by the machine learning research community.
  • Speech and Voice Technologies3 sub-tagsTools and architectures for speech synthesis, voice interaction, and audio-based AI applications.
  • Studio Interfaces1 sub-tagIntegrated development environments and graphical interfaces designed for building, testing, and deploying artificial intelligence applications.
  • Synthetic Data2 sub-tagsTools and methodologies for generating artificial datasets to train models when real-world data is scarce or sensitive.