Learn how to develop, deploy and iterate on production-grade ML applications.
Repository Index
47,133 repositories indexed
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📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
- applied-machine-learning
- production
- applied-data-science
- machine-learning
The 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.
- metadata
- datadiscovery
- dataquality
- data-profiling
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
- pandas-profiling
- pandas-dataframe
- statistics
- jupyter-notebook
Always know what to expect from your data.
- pipeline-tests
- dataquality
- datacleaning
- datacleaner
Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
- weak-supervision
- data-cleaning
- data-quality
- noisy-labels
Refine high-quality datasets and visual AI models
Evidently 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.
- data-drift
- jupyter-notebook
- pandas-dataframe
- machine-learning
The Open Source Feature Store for AI/ML
- machine-learning
- features
- ml
- big-data
lakeFS - Data version control for your data lake | Git for data
- data-engineering
- data-versioning
- go
- object-storage
Open-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.
- data-engineering
- data-integration
- data-pipeline
- data-quality
Engine for AI/ML/Data tracking, visualization, explainability, drift detection, and dashboards for Polyaxon.
- pandas
- pandas-summary
- dataframes
- data-science
Data validation toolkit for assessing and monitoring data quality.
- data-validation
- tabular-data
- data-testing
- data-quality
Data Quality and Observability platform for the whole data lifecycle, from profiling new data sources to full automation with Data Observability. Configure data quality checks from the UI or in YAML files, let DQOps run the data quality checks daily to detect data quality issues.
- data-ops
- data-quality
- data-quality-checks
- data-quality-measurement
Lightweight DataFrame validation decorators for Pandas, Polars, Modin, and PyArrow. No custom types required.
Declarative data quality engine. Define checks in YAML, run anywhere.
- airflow
- anomaly-detection
- data-contracts
- data-quality
A detective for your data. Zero-config data quality monitoring — works with dbt, Postgres, BigQuery, Snowflake. No YAML.
- anomaly-detection
- bigquery
- cli
- data-engineering
Blazingly fast data comparison tool for Python, powered by Rust. Compare massive CSV/Parquet datasets instantly.
Open, audit-grade agentic data quality framework with portable industry packs