Repository Index

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

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

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

• machine-learning
• ml
• model-validation
• data-validation

Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.

• dataprep
• data-science
• datapreparation
• dataconnector

Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.

• analytics
• bigquery
• data-modeling
• data-pipelines

Utility to compare data between homogeneous or heterogeneous environments to ensure source and target tables match

The repository host gives no description.

• hacktoberfest
• data
• datalineage
• dbt

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

Declarative data quality engine. Define checks in YAML, run anywhere.

• airflow
• anomaly-detection
• data-contracts
• data-quality