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
AWS Identity and Access Management Visualizer and Anomaly Finder
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.
YALIH (Yet Another Low Interaction Honeyclient) is a low Interaction Client honeypot designed to detect malicious websites through signature, anomaly and pattern matching techniques
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.