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Transform raw data into ML-ready features with efficient single-pass processing, distribution-aware encoding, and production-ready deployment.

A curated collection of production-ready Keras models, layers, and architectural patterns for rapid ML development.

Build and execute complex data pipelines with graph-based orchestration for scalable and maintainable workflows.

Reusable modular, mix-and-match ML building blocks that work across **Keras, TensorFlow, and PyTorch**

FlowyML is an open-source, production-ready, and extensible ML pipeline framework that empowers data scientists and engineers to build, deploy, and manage machine learning pipelines with ease.

A PyTorch-based tabular data preprocessing library inspired by Keras Data Preprocessor (KDP), bringing powerful data preprocessing capabilities to the PyTorch ecosystem.