开源序

All projects

Repositories in this selection 17 · UTC 2026-11-03

This page · fastest this week—Insufficient history
7-day net stars—Observed growth coverage 0/17
Pushed in the last 14 days7 / 17
Commercial use
More filters
Loading…Recently collected
CompareRankProjectStarFork30-day trend7-day net changeLast pushSign in to save
1GokuMohandas / Made-With-MLPractical material on building, deploying and iterating ML applications.Jupyter NotebookMIT · PermissiveInsufficient rank history49,9047,814——2026-03-04
2eugeneyan / applied-ml📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.UnknownMIT · PermissiveInsufficient rank history30,7814,050——2024-07-18
3open-metadata / OpenMetadataThe Open Context Layer for Data and AI , OpenMetadata is the open platform for building trusted data context and business semantics for humans, AI assistants, and agents.TypeScriptApache-2.0 · PermissiveInsufficient rank history15,6652,496——2026-11-03
4Data-Centric-AI-Community / fg-data-profiling1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.PythonMIT · PermissiveInsufficient rank history13,7451,803——2026-11-02
5fivetran / great_expectationsAlways know what to expect from your data.PythonApache-2.0 · PermissiveInsufficient rank history11,9141,882——2026-11-02
6cleanlab / cleanlabCleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.PythonApache-2.0 · PermissiveInsufficient rank history11,728937——2026-01-13
7voxel51 / fiftyoneRefine high-quality datasets and visual AI modelsTypeScriptApache-2.0 · PermissiveInsufficient rank history11,266842——2026-11-03
8evidentlyai / evidentlyEvidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.Jupyter NotebookApache-2.0 · PermissiveInsufficient rank history8,032964——2026-09-29
9feast-dev / feastThe Open Source Feature Store for AI/MLPythonApache-2.0 · PermissiveInsufficient rank history7,3531,490——2026-11-01
10treeverse / lakeFSlakeFS - Data version control for your data lake | Git for dataGoNOASSERTION · Restricted / unknownInsufficient rank history5,575490——2026-11-01
11GokuMohandas / mlops-courseLearn how to design, develop, deploy and iterate on production-grade ML applications.Jupyter NotebookMIT · PermissiveInsufficient rank history3,414608——2024-08-16
12whylabs / whylogsAn open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈Jupyter NotebookApache-2.0 · PermissiveInsufficient rank history2,837144——2025-01-10
13featureform / featureformThe Virtual Feature Store. Turn your existing data infrastructure into a feature store.GoMPL-2.0 · Share derivative sourceInsufficient rank history1,991109——2025-07-03
14slothflowlabs / duckleOpen-source ETL/ELT you deploy on your own servers or cloud. Built on DuckDB: no-code/low-code visual pipelines or SQL, 385 components, dbt, CDC, data quality, reverse ETL, lineage, MCP for AI agents. No vendor cloud, no per-row billing.RustApache-2.0 · PermissiveInsufficient rank history1,546120——2026-11-01
15InfuseAI / piperiderCode review for data in dbtPythonApache-2.0 · PermissiveInsufficient rank history49324——2025-01-03
16wzn1118 / AsteriaAnalystEnterprise Data Analysis, Statistical Analysis, Data Visualization and Management Reporting Workbench |Analysis Lab, Traceable Evidence, FastAPI, Next.js, Windows.PythonUnknown · Restricted / unknownInsufficient rank history2863——2026-07-28
17Seddryck / NBiNBi is a testing framework (add-on to NUnit) for Business Intelligence and Data Access. The main goal of this framework is to let users create tests with a declarative approach based on an Xml syntax. By the means of NBi, you don't need to develop C# or Java code to specify your tests! Either, you don't need Visual Studio or Eclipse to compile your test suite. Just create an Xml file and let the framework interpret it and play your tests. The framework is designed as an add-on of NUnit but with the possibility to port it easily to other testing frameworks.C#Apache-2.0 · PermissiveInsufficient rank history10638——2026-06-20
Ranked by repository stars, one position per repository. Stars and forks are not user counts.1 / 1

License tiers are derived from metadata. Check obligations for your use; unknown does not mean prohibited.