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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.

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.

The collection of pre-trained, state-of-the-art AI models for ailia SDK

Anomaly Detection and Correlation library

ML powered analytics engine for outlier detection and root cause analysis.

Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.

A Python 3 library making time series data mining tasks, utilizing matrix profile algorithms, accessible to everyone.

A distributed Spark/Scala implementation of the isolation forest and extended isolation forest algorithms for unsupervised outlier detection, featuring support for scalable training and ONNX export for easy cross-platform inference.

Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.

Local safety layer for AI agents that use the terminal. Screens risky commands and MCP/tool calls, watches Linux activity with eBPF, blocks dangerous behavior, and keeps audit trails local. Open source, self-hosted, dry-run by default.

Global maritime intelligence platform for real-time vessel tracking, AIS data analysis, sanctions monitoring, shipping routes, port activity, anomaly detection, OSINT analytics, and geospatial insights

Detection of rootkit file hiding activities through analysis of shifts in kernel function execution times.

Detects structural waste in cloud billing exports (AWS/GCP/Azure) using rolling-median + MAD, robust to the masking effect that breaks mean+stddev anomaly detection. Python library, CLI, FastAPI service, and GitHub Action.

Python SDK for WaveGuard physics-based anomaly detection API. One call. Any data.

Multi-cloud cost management MCP server (Azure + GCP). Read-only access to spending, anomalies, forecasts, budgets, and guided FinOps workflows. Ask your AI about your cloud bill.