Machine learning experiment tracking and model development platform with run comparisons, hyperparameter optimization, evaluation tables, and collaborative workflows.

Open-source platform for tracking machine learning experiments, evaluating models, managing versions and lineage, and preparing models for deployment.

Distributed machine learning and AutoML engine with Python, R, and Flow interfaces, automated model comparison, explainability, and a separate enterprise Secure edition.

Open-source gradient boosting library for classification, regression, and ranking, with Python and R interfaces, GPU acceleration, and distributed training support.

Open-source machine learning framework for building and training models, preparing data, and deploying inference across server, browser, mobile, and cloud environments.