1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
- pandas-profiling
- pandas-dataframe
- statistics
- jupyter-notebook
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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
Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
- dataquality
- spark
- unit-testing
- scala
Library for exploring and validating machine learning data
pyspark methods to enhance developer productivity 📣 👯 🎉