awesome-repositories.com
© 2026 Bringes Technology SRL·VAT RO45896025·hello@bringes.io
MCPSitemapPrivacyTerms
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.

  1. Home
  2. Artificial Intelligence & ML

Awesome Artificial Intelligence & ML GitHub Repositories

Describe the repository you're looking for…
We'll search the best matching repositories with AI.
  • commaai/openpilot

    commaai/openpilot

    60,104GitHubView on GitHub↗

    Openpilot is an open-source driver assistance system that integrates with vehicle control units to provide automated steering, acceleration, and braking. It functions as an automotive robotics middleware, utilizing a specialized runtime environment to process sensor data and execute real-time control commands that mana

    Pythonadvanced-driver-assistance-systemsdriver-assistance-systemsrobotics
  • pathwaycom/pathway

    pathwaycom/pathway

    59,684GitHubView on GitHub↗

    Pathway is a high-performance data processing framework designed for building unified batch and streaming pipelines. It functions as an orchestrator for complex data transformations, utilizing a differential dataflow engine to process updates incrementally. By treating static datasets and continuous event streams with

    Pythonbatch-processingdata-analyticsdata-pipelines
  • nuxt/nuxt

    nuxt/nuxt

    59,659GitHubView on GitHub↗

    Nuxt is a universal web framework designed for building full-stack applications that seamlessly transition between server-side rendering and client-side interactivity. It provides a comprehensive development environment that automates routing, dependency injection, and type generation, allowing developers to focus on a

    TypeScriptcsrframeworkfull-stack
  • CorentinJ/Real-Time-Voice-Cloning

    CorentinJ/Real-Time-Voice-Cloning

    59,355GitHubView on GitHub↗

    This project is a neural text-to-speech engine and voice cloning toolkit designed to generate synthetic speech that mimics the vocal characteristics of a target speaker. It functions as a real-time audio synthesizer, utilizing a deep learning pipeline to convert written text into high-fidelity speech output with minima

    Pythondeep-learningpythonpytorch
  • meta-llama/llama

    meta-llama/llama

    59,157GitHubView on GitHub↗

    Llama is a computational framework and runtime environment designed for executing transformer-based neural networks locally. It functions as a generative AI inference engine, enabling the processing of input sequences through pre-trained model weights to produce text completions and structured data outputs directly on

    Python
  • Solido/awesome-flutter

    Solido/awesome-flutter

    59,015GitHubView on GitHub↗

    This project is a community-curated directory of resources, libraries, and tools designed to support developers working with the Flutter framework. It functions as a centralized knowledge base, organizing high-quality external references into a structured, human-readable format to assist in the discovery of technical m

    Dartandroidawesomeawesome-list
  • PlexPt/awesome-chatgpt-prompts-zh

    PlexPt/awesome-chatgpt-prompts-zh

    58,347GitHubView on GitHub↗

    This project is a community-driven library of structured text inputs designed to guide large language models into specific roles, behaviors, and operational modes. It functions as a comprehensive repository of prompt engineering resources, providing reusable templates that allow users to override default model tendenci

    chat-gptchatgptchatgpt3
  • cline/cline

    cline/cline

    58,164GitHubView on GitHub↗

    Cline is an extensible agent runtime and multi-agent orchestration engine designed to automate complex software engineering workflows. It functions as an integrated development environment extension that bridges strategic task planning with autonomous execution, allowing users to manage multi-step projects through huma

    TypeScript
  • sharkdp/bat

    sharkdp/bat

    57,298GitHubView on GitHub↗

    This project is a command-line text viewer designed to enhance terminal output through automatic syntax highlighting and integrated file management. It functions as a replacement for standard system pagers, providing a readable interface for large text streams, source code, and markup files by applying color-coded form

    Rustclicommand-linegit
  • zylon-ai/private-gpt

    zylon-ai/private-gpt

    57,116GitHubView on GitHub↗

    This project is a privacy-first backend service designed to facilitate retrieval-augmented generation by processing local documents into searchable vector representations. It provides a modular architecture that allows users to ingest diverse file formats, manage document metadata, and perform semantic searches to prov

    Python
  • ultralytics/yolov5

    ultralytics/yolov5

    56,830GitHubView on GitHub↗

    YOLOv5 is a comprehensive computer vision framework designed for end-to-end deep learning, specializing in real-time object detection, image classification, and instance segmentation. It provides a unified toolkit that manages the entire lifecycle of a model, from initial dataset configuration and hyperparameter tuning

    Pythoncoremldeep-learningios
  • pathwaycom/llm-app

    pathwaycom/llm-app

    56,311GitHubView on GitHub↗

    This project is a data processing engine and AI application platform designed for building production-grade machine learning workflows. It provides a unified programming model that handles both historical batch data and live stream ingestion, enabling the development of real-time ETL pipelines and scalable data transfo

    Jupyter Notebookchatbothugging-facellm
  • meilisearch/meilisearch

    meilisearch/meilisearch

    55,992GitHubView on GitHub↗

    Meilisearch is a Rust-based search engine providing typo-tolerant full-text and vector-based semantic search with real-time conversational capabilities.

    Rustaiapiapp-search
  • tiimgreen/github-cheat-sheet

    tiimgreen/github-cheat-sheet

    55,238GitHubView on GitHub↗

    This project is a community-driven knowledge base that serves as a comprehensive reference guide for Git and GitHub. It functions as both a command-line cheat sheet for terminal-based version control operations and a collaborative workflow resource detailing platform-specific conventions for managing repositories, issu

    awesomeawesome-listgit
  • AntonOsika/gpt-engineer

    AntonOsika/gpt-engineer

    55,201GitHubView on GitHub↗

    GPT-Engineer is an autonomous agent and framework designed for AI-assisted software development. It functions as a generative codebase architect that translates natural language requirements into complete, functional software projects by reading and writing files directly to the local file system. The platform disting

    Pythonaiautonomous-agentcode-generation
  • RVC-Boss/GPT-SoVITS

    RVC-Boss/GPT-SoVITS

    55,111GitHubView on GitHub↗

    GPT-SoVITS is a text-to-speech synthesis engine and voice cloning toolkit designed for generating natural-sounding human speech. It functions as a neural audio processing pipeline that maps input text to high-fidelity audio waveforms, utilizing conditional variational autoencoders and flow-based decoders to ensure expr

    Pythontext-to-speechttsvits
  • deepfakes/faceswap

    deepfakes/faceswap

    54,974GitHubView on GitHub↗

    Faceswap is a comprehensive framework for automated media manipulation and neural face synthesis. It provides a modular pipeline that manages the entire lifecycle of facial feature extraction, deep learning model training, and image conversion. By coordinating complex computer vision workflows, the system enables users

    Pythondeep-face-swapdeep-learningdeep-neural-networks
  • appwrite/appwrite

    appwrite/appwrite

    54,884GitHubView on GitHub↗

    Appwrite is a backend-as-a-service platform that provides a unified development environment for building full-stack applications. It integrates essential infrastructure components—including authentication, databases, storage, and serverless functions—into a single, centralized interface to simplify application developm

    TypeScriptandroidappwritebackend
  • Mintplex-Labs/anything-llm

    Mintplex-Labs/anything-llm

    54,751GitHubView on GitHub↗

    This platform serves as a comprehensive environment for managing private language models, document knowledge bases, and automated agent workflows within secure local infrastructure. It functions as a document-aware workspace that enables users to ingest diverse file formats into searchable repositories, ensuring that a

    JavaScriptai-agentscustom-ai-agentsdeepseek
  • microsoft/autogen

    microsoft/autogen

    54,656GitHubView on GitHub↗

    This framework provides a development environment for building collaborative systems where autonomous agents interact to solve complex tasks through conversational workflows. It functions as a conversational workflow engine and event-driven runtime, coordinating multi-step processes by translating high-level goals into

    Pythonagenticagentic-agiagents
Prev1…678Next

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.