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121 dépôts

Awesome GitHub RepositoriesData Collections & Datasets

This group comprises various types of data collections and datasets, including domain-specific and open data.

Explore 121 awesome GitHub repositories matching data & databases · Data Collections & Datasets. Refine with filters or upvote what's useful.

Awesome Data Collections & Datasets GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • kamranahmedse/developer-roadmapAvatar de kamranahmedse

    kamranahmedse/developer-roadmap

    357,434Voir sur GitHub↗

    Developer Roadmap est une plateforme pilotée par la communauté qui fournit des parcours d'apprentissage structurés basés sur des graphes pour le génie logiciel. Elle sert de dépôt de connaissances complet où les domaines techniques sont organisés en séquences visuelles pour guider l'acquisition de compétences professionnelles et la croissance de carrière. Le projet se distingue par un écosystème collaboratif qui permet aux utilisateurs de contribuer à des roadmaps, d'organiser les meilleures pratiques de l'industrie et de maintenir des profils professionnels. Il intègre des cadres d'évaluation diagnostique pour évaluer la compétence technique, aidant les développeurs à identifier les lacunes en matière de connaissances et à se préparer aux entretiens professionnels grâce à des séquences d'apprentissage ciblées. Au-delà de ses capacités de cartographie de base, la plateforme propose des idées de projets pratiques et du tutorat interactif pour renforcer les concepts d'ingénierie. Elle offre un espace centralisé pour que la communauté puisse partager des ressources, suivre le développement progressif des compétences et naviguer dans des paysages techniques complexes.

    Maintains clean datasets for community-contributed roadmap content.

    TypeScriptangular-roadmapbackend-roadmapblockchain-roadmap
    Voir sur GitHub↗357,434
  • awesome-selfhosted/awesome-selfhostedAvatar de awesome-selfhosted

    awesome-selfhosted/awesome-selfhosted

    299,516Voir sur GitHub↗

    Ce projet est un répertoire de logiciels open source organisé par la communauté, conçu pour être déployé dans des environnements de serveurs privés et des laboratoires domestiques. Il sert de ressource complète pour découvrir des alternatives indépendantes et auto-hébergées aux services cloud grand public, permettant aux utilisateurs de conserver la pleine propriété des données et le contrôle de leur infrastructure numérique. Le répertoire est structuré par une taxonomie hiérarchique qui organise une vaste collection d'applications en catégories logiques, allant de la gestion multimédia et de l'analyse de données à la communication privée et aux outils de productivité d'équipe. Il se distingue par un processus de revue par les pairs collaboratif, où les membres de la communauté valident la qualité et la pertinence de chaque soumission pour garantir que le répertoire reste précis et fiable. Le projet couvre une large surface de capacités, notamment l'automatisation de l'infrastructure, le déploiement de services basés sur des conteneurs et la gestion de configuration déclarative. Ces outils aident les utilisateurs à maintenir des environnements de serveur reproductibles et à gérer des dépendances de services complexes sur du matériel privé. Le répertoire est maintenu en tant que dépôt contrôlé par version, garantissant que toutes les mises à jour et les changements pilotés par la communauté sont suivis et transparents.

    Creates websites for hosting and sharing open datasets to facilitate public access and transparency.

    awesomeawesome-listcloud
    Voir sur GitHub↗299,516
  • iptv-org/iptvAvatar de iptv-org

    iptv-org/iptv

    127,909Voir sur GitHub↗

    This project is a community-maintained, open-source repository that functions as a centralized directory for streaming metadata. It aggregates publicly available network stream links and organizes them into standardized, machine-readable playlist formats. By acting strictly as a metadata-only index, the platform enables users to access and organize live broadcast content across various third-party media playback applications without hosting or distributing any actual video files. The repository distinguishes itself through a collaborative, crowdsourced workflow where contributors actively mai

    Coordinates community contributions to build and maintain a collaborative, centralized database of external streaming resources.

    TypeScriptiptvm3uplaylist
    Voir sur GitHub↗127,909
  • openai/whisperAvatar de openai

    openai/whisper

    102,828Voir sur 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 capable of performing simultaneous transcription, language identification, and translation. The system distinguishes itself through a unified multi-task modeling approach that shares token sequences across different objectives, allowing it to handle diverse languages and vocabularies

    Contains English-only speech corpora suitable for rapid testing and validation of speech-to-text models.

    Python
    Voir sur GitHub↗102,828
  • punkpeye/awesome-mcp-serversAvatar de punkpeye

    punkpeye/awesome-mcp-servers

    89,264Voir sur GitHub↗

    This project serves as a centralized directory and interoperability hub for the Model Context Protocol, providing a curated collection of standardized service connectors that bridge artificial intelligence models with external software, databases, and APIs. It facilitates the integration of AI agents with diverse ecosystems by offering a registry of machine-readable interface definitions that enable dynamic tool discovery and structured context injection. The directory distinguishes itself by focusing on the protocol-based interoperability required for autonomous AI agents to interact with he

    Connects analytical databases and data platforms to enable natural language querying and automated data visualization.

    aimcp
    Voir sur GitHub↗89,264
  • d2l-ai/d2l-zhAvatar de d2l-ai

    d2l-ai/d2l-zh

    78,493Voir sur GitHub↗

    This project is an open-source, interactive educational platform designed to teach deep learning through a comprehensive, code-first curriculum. It provides a structured learning path that covers foundational mathematics, modern neural network architectures, and practical optimization techniques, enabling practitioners to master complex artificial intelligence concepts through hands-on experimentation. The platform distinguishes itself by integrating technical explanations with executable Jupyter notebooks. This design allows readers to modify code and hyperparameters in real-time, facilitati

    Provides curated datasets and processing pipelines for training and evaluating semantic word embeddings.

    Pythonbookchinesecomputer-vision
    Voir sur GitHub↗78,493
  • elastic/elasticsearchAvatar de elastic

    elastic/elasticsearch

    77,012Voir sur GitHub↗

    Elasticsearch is a distributed search engine and document store designed for the high-performance indexing and retrieval of massive volumes of unstructured data. It functions as a centralized analytics platform, providing a schema-flexible architecture that organizes information into searchable indices while maintaining global cluster state through a distributed consensus mechanism. The platform distinguishes itself through its integrated approach to observability, security, and advanced analytics. It combines full-text, vector, and hybrid search capabilities with machine learning-driven insi

    Aggregates large-scale data to provide a centralized platform for statistical analysis and insight generation.

    Javaelasticsearchjavasearch-engine
    Voir sur GitHub↗77,012
  • awesomedata/awesome-public-datasetsAvatar de awesomedata

    awesomedata/awesome-public-datasets

    75,979Voir sur GitHub↗

    This project is a community-maintained, open-access directory of high-quality public datasets. It serves as a centralized reference point for researchers, developers, and data scientists to locate reliable information sources across a wide spectrum of industries and scientific fields. By providing a structured index, the repository facilitates the discovery of data necessary for exploratory analysis, machine learning model training, and the development of data-intensive applications. The directory distinguishes itself through a lightweight, platform-agnostic approach to resource indexing that

    Acts as a centralized reference point for locating domain-specific datasets across government, scientific, and technological sectors.

    aaron-swartzawesome-public-datasetsdatasets
    Voir sur GitHub↗75,979
  • grafana/grafanaAvatar de grafana

    grafana/grafana

    74,456Voir sur GitHub↗

    Grafana is an observability data platform designed to aggregate metrics, logs, and traces from diverse sources into a unified environment. It functions as a centralized interface for visualizing complex telemetry data, transforming raw streams into interactive dashboards that support real-time system health tracking and performance monitoring. The platform distinguishes itself through a plugin-based modular architecture that integrates disparate databases, cloud services, and monitoring tools via a standardized data abstraction layer. This framework allows for the dynamic loading of external

    Unifies metrics, logs, and traces into a single environment to simplify monitoring and analysis across diverse data sources.

    TypeScriptalertinganalyticsbusiness-intelligence
    Voir sur GitHub↗74,456
  • apache/supersetAvatar de apache

    apache/superset

    73,451Voir sur GitHub↗

    Superset is a web-based business intelligence platform designed for data exploration, visualization, and interactive dashboarding. It functions as a query-driven analytics engine that connects to various SQL databases, allowing users to perform ad-hoc analysis, define virtual metrics, and build complex data visualizations through a centralized interface. The platform distinguishes itself through a robust semantic layer that transforms raw database schemas into calculated columns and virtual metrics, enabling consistent business logic across an organization. It features a plugin-based visualiz

    Acts as a centralized hub for managing organizational data assets, enforcing security policies, and distributing automated reports.

    TypeScriptanalyticsapacheapache-superset
    Voir sur GitHub↗73,451
  • openbb-finance/openbbAvatar de OpenBB-finance

    OpenBB-finance/OpenBB

    69,583Voir sur GitHub↗

    OpenBB is a financial data platform and investment research terminal designed to aggregate, normalize, and distribute market data across analytical workflows. It functions as a comprehensive ecosystem that bridges disparate financial data providers with custom applications, spreadsheets, and internal modeling infrastructure. The platform distinguishes itself through a provider-based data abstraction layer that normalizes heterogeneous financial APIs into a consistent, schema-driven format. This architecture supports quantitative research automation and the construction of interactive, widget-

    Aggregates, normalizes, and distributes diverse market data for use in financial research and analytical applications.

    Pythonaicryptoderivatives
    Voir sur GitHub↗69,583
  • openbb-finance/openbbterminalAvatar de OpenBB-finance

    OpenBB-finance/OpenBBTerminal

    69,303Voir sur GitHub↗

    OpenBBTerminal is a Python financial data platform and command line interface designed for aggregating and analyzing market data from diverse APIs. It serves as a quantitative analysis tool for processing stock, crypto, and derivative datasets to identify market trends and build investment strategies. The project utilizes a pluggable financial API framework with an adapter-based architecture, allowing external financial data providers to be integrated as independent modules. This system standardizes information from public and proprietary sources into a unified layer to support cross-asset an

    Serves as a comprehensive ecosystem for aggregating and analyzing market data from diverse APIs for quantitative research.

    Python
    Voir sur GitHub↗69,303
  • nocodb/nocodbAvatar de nocodb

    nocodb/nocodb

    63,466Voir sur GitHub↗

    NocoDB is a visual platform that transforms relational databases into collaborative, spreadsheet-style workspaces. By acting as a headless database backend, it provides a unified environment for designing database structures, managing record relationships, and interacting with data without requiring manual SQL queries. The platform normalizes interactions across various SQL and NoSQL data sources, allowing users to manage complex datasets through a centralized interface. The project distinguishes itself by automatically generating RESTful and GraphQL APIs from existing database schemas, enabl

    Serves as a primary container for organizing datasets and managing their associated configurations in one location.

    TypeScriptairtableairtable-alternativeautomatic-api
    Voir sur GitHub↗63,466
  • ultralytics/ultralyticsAvatar de ultralytics

    ultralytics/ultralytics

    58,468Voir sur GitHub↗

    Ultralytics is a comprehensive computer vision framework designed for training, validating, and deploying deep learning models across a wide range of visual recognition tasks. It provides a unified interface for core operations including object detection, instance segmentation, pose estimation, and image classification. By utilizing a modular architecture, the platform allows users to swap model components to balance inference speed and accuracy requirements for diverse applications. The framework distinguishes itself through its support for real-time processing and flexible deployment. It in

    Retrieves diverse classification datasets, ranging from standard benchmarks to large-scale image collections, for training categorization models.

    Pythonclicomputer-visiondeep-learning
    Voir sur GitHub↗58,468
  • ngosang/trackerslistAvatar de ngosang

    ngosang/trackerslist

    54,183Voir sur GitHub↗

    This project is a curated, community-driven registry of public BitTorrent trackers designed to facilitate peer-to-peer file sharing. It serves as a centralized resource for network endpoints that coordinate connections between distributed clients, helping users discover and maintain reliable infrastructure for decentralized communication protocols. The repository distinguishes itself through a fully automated orchestration pipeline that ensures the lists remain current and accurate. Every day, background tasks perform distributed health monitoring to verify connectivity and filter out unrespo

    Aggregates and automatically refreshes a comprehensive collection of public URLs for decentralized file sharing.

    bittorrentbittorrent-trackerbittorrent-trackers
    Voir sur GitHub↗54,183
  • thealgorithms/javascriptAvatar de TheAlgorithms

    TheAlgorithms/JavaScript

    34,180Voir sur GitHub↗

    This project is an educational code repository providing a curated collection of common algorithms and data structures implemented in JavaScript. It serves as a reference library and a study resource for learning computer science concepts and foundational programming principles. The repository focuses on the practical implementation of standard data structures and algorithmic patterns. It provides a codebase for studying computational problem-solving and practicing the technical requirements often found in software engineering interviews. The codebase covers core data structure implementatio

    Provides implementations of fundamental data structures like hash tables, lists, and sets.

    JavaScriptalgorithmalgorithm-challengesalgorithms
    Voir sur GitHub↗34,180
  • xiu2/trackerslistcollectionAvatar de XIU2

    XIU2/TrackersListCollection

    31,531Voir sur GitHub↗

    TrackersListCollection is an automated aggregator that maintains a directory of active BitTorrent tracker addresses. It functions as a resource for peer-to-peer file sharing applications, providing the necessary endpoints to facilitate peer discovery and improve network connectivity. The project distinguishes itself through a combination of automated source aggregation and community-driven curation, which ensures the repository remains populated with healthy network nodes. By consolidating data from multiple public endpoints, it provides a centralized source for maintaining current and reliab

    Maintains a curated directory of active BitTorrent tracker nodes to improve peer discovery and network connectivity.

    aria2aria2-format-trackerbittorrent
    Voir sur GitHub↗31,531
  • d2l-ai/d2l-enAvatar de d2l-ai

    d2l-ai/d2l-en

    29,001Voir sur GitHub↗

    This project is an educational platform and research toolkit designed to teach deep learning through a combination of mathematical theory, visual diagrams, and executable code. It provides a comprehensive environment for building, training, and evaluating neural networks, grounding complex concepts in interactive computational notebooks that allow for hands-on experimentation. The framework distinguishes itself by interleaving theoretical foundations—including linear algebra, calculus, and probability—with practical implementations across multiple industry-standard libraries. It supports flex

    Downloads and extracts structured advertising data containing categorical features and click-through labels.

    Pythonbookcomputer-visiondata-science
    Voir sur GitHub↗29,001
  • openzeppelin/openzeppelin-contractsAvatar de OpenZeppelin

    OpenZeppelin/openzeppelin-contracts

    27,157Voir sur GitHub↗

    OpenZeppelin Contracts is a library of modular, secure, and reusable smart contract components designed for the development of decentralized applications. It provides a foundational framework for building standard-compliant contracts, offering battle-tested implementations for token standards, access control, and common utility patterns. The project distinguishes itself through its comprehensive support for complex architectural patterns, including proxy-based upgradeability, role-based access control, and account abstraction. It enables developers to implement modular logic injection via hoo

    Provides optimized, enumerable data structures for efficient storage and retrieval of contract data.

    Solidityethereumevmsecurity
    Voir sur GitHub↗27,157
  • walter201230/pythonAvatar de walter201230

    walter201230/Python

    26,516Voir sur GitHub↗

    Python is a high-level, interpreted programming language designed for readability and versatility. It operates via a bytecode-based virtual machine and manages memory automatically through reference-counting garbage collection. The language supports multiple programming paradigms, including object-oriented, imperative, and functional styles, and provides a comprehensive standard library for system operations, networking, and data handling. The language is distinguished by its dynamic nature, allowing for runtime object introspection and metaclass-driven class creation. It utilizes protocol-ba

    Python creates read-only sets that can be used as dictionary keys or nested within other collections without risk of modification.

    Pythonpythonpython3
    Voir sur GitHub↗26,516
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  2. Data & Databases
  3. Data Collections & Datasets

Explorer les sous-tags

  • Advertising DatasetsStructured datasets containing categorical features and click-through labels for predictive modeling. **Distinct from Advertising Analytics:** Focuses on ad-specific datasets rather than general data collections.
  • Analytics Data PlatformsCentralized systems for large-scale data aggregation and insight generation.
  • BasesPrimary containers for grouping datasets and their associated configurations.
  • Benchmark Dataset CollectionGathering real-world issue and patch pairs to create software engineering benchmarks. **Distinct from Data Collections & Datasets:** Specializes in collecting bug-fix pairs from version control for benchmarking, not general data collection.
  • BitTorrent Tracker ListsAggregated lists of public BitTorrent tracker URLs used for peer-to-peer file sharing.
  • Classification Datasets1 sous-tagCollections of labeled images used for training categorization models.
  • Collaborative Data AggregatorsPlatforms where community members contribute to and maintain centralized databases of external resource links.
  • Collection Lifecycle Management3 sous-tagsUtilities for managing the lifecycle of database collections including resource cleanup. **Distinct from Data Collections & Datasets:** Focuses on collection lifecycle management, distinct from general data collections.
  • Contract Data CollectionsProvides enumerable data structures for efficient storage and retrieval of contract-specific data. **Distinct from Data Collections & Datasets:** Distinct from Data Collections & Datasets: focuses on on-chain enumerable structures rather than general datasets.
  • Conversational Data ExplorationInteractive chat interfaces for querying and explaining datasets. **Distinct from Data Collections & Datasets:** Distinct from Dataset Processors: focuses on natural language interaction with data rather than programmatic transformation.
  • Cross-Source Joins2 sous-tagsCapabilities for performing analytical operations across multiple disparate data sources simultaneously. **Distinct from Data Collections & Datasets:** Focuses on the join and cross-source analytical capability, distinct from static dataset collections.
  • Dataset ComparatorsUtilities for evaluating differences and statistical drift between multiple versions of data collections. **Distinct from Data Collections & Datasets:** Distinct from Data Collections & Datasets: focuses on the comparison logic between versions rather than the storage of the collections themselves.
  • Dataset Creation3 sous-tagsTools for selecting tables from connected sources to define reporting scopes. **Distinct from Data Collections & Datasets:** Distinct from Data Collections & Datasets: focuses on the creation process rather than the collection itself.
  • Dataset Processors1 sous-tagUtilities for iterating over and transforming entries within a data collection. **Distinct from Data Collections & Datasets:** Distinct from Data Collections & Datasets: focuses on the processing logic applied to entries rather than the collection itself.
  • Dataset Reshapers1 sous-tagTools for merging, concatenating, and pivoting distributed collections. **Distinct from Data Collections & Datasets:** Focuses on reshaping for analysis, distinct from general dataset collections.
  • Enterprise Data PortalsCentralized hubs for data asset management, reporting, and organizational access control.
  • Financial Data PlatformsEcosystems for aggregating and distributing market data.
  • Immutable Sets4 sous-tagsRead-only collection types that support hashing for use as dictionary keys or nested elements. **Distinct from Data Collections & Datasets:** Distinct from Data Collections & Datasets: focuses specifically on immutable set types rather than general data collections.
  • Knowledge Discovery Resources9 sous-tagsCentralized repositories or directories used to locate and access domain-specific datasets.
  • Observability Data PlatformsCentralized environments for aggregating and visualizing telemetry data.
  • Open Data Services1 sous-tagAPIs for querying public-sector and government-provided information.
  • Persistent Collections1 sous-tagImmutable collections that preserve prior versions on modification for safe concurrent and functional programming. **Distinct from Data Collections & Datasets:** Distinct from Data Collections & Datasets: focuses on persistent, version-preserving immutable collections rather than general data storage.
  • Speech CorporaDatasets containing audio recordings and associated transcripts.
  • Standard Data Structures1 sous-tagImplementations of fundamental data structures like hash tables, lists, and sets. **Distinct from Data Collections & Datasets:** Distinct from general datasets: focuses on language-level primitive data structures rather than external data collections.
  • Visual Dataset CollectionCapturing and saving screen frames during interaction to create labeled datasets for ML training. **Distinct from Data Collections & Datasets:** Specializes dataset collection specifically for visual frames captured from a user interface.
  • Word Embedding DatasetsDatasets specifically curated for training or evaluating word vector representations and semantic language models.