Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.

A Python library for anomaly detection across tabular, time series, graph, text, and image data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.

A unified framework for machine learning with time series

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

Deep Learning for humans

We write your reusable computer vision tools. 💜

💫 Industrial-strength Natural Language Processing (NLP) in Python

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Low-code framework for building custom LLMs, neural networks, and other AI models

Fast and Accurate ML in 3 Lines of Code

A python library for user-friendly forecasting and anomaly detection on time series.

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.