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
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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.
A unified framework for machine learning with time series
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
A python library for user-friendly forecasting and anomaly detection on time series.
Anomaly Detection and Correlation library
TranslatedAn industrial anomaly detection project based on PatchCore, studying layer2/layer3 score fusion, sensitivity-guided shrinkage, and risk-controlled gating, and providing an engineering-oriented Streamlit demo.
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
Lightweight Docker monitoring dashboard with anomaly detection & Telegram alerts. One-liner install, zero config.
Declarative data quality engine. Define checks in YAML, run anywhere.
A detective for your data. Zero-config data quality monitoring — works with dbt, Postgres, BigQuery, Snowflake. No YAML.