A fast, open-source Rust solution for building scalable machine learning models with easy-to-use, customizable APIs and comprehensive tools.

Built with Rust, Delta delivers high-performance machine learning, optimized for compute-intensive tasks on CPU and future GPU backends.

Simple APIs make Delta accessible for beginners, with flexible options for advanced users to customize ML workflows.

Modular design allows users to extend Delta with custom preprocessing, algorithms, or evaluation metrics tailored to ML needs.

Supports a growing suite of classical ML algorithms, including Linear Regression, Decision Trees, Random Forest, SVM, KNN, and more, with expansions like Naive Bayes and Gradient Boosting.

Currently supports CPU, with planned support for Metal, CUDA, Vulkan, and more, enabling efficient classical ML across diverse hardware.

Seamless access to datasets pre-trained models via Nebula, enhancing collaboration and reproducibility.

Future parallel and distributed training for classical ML, evolving to support large-scale deep learning models across multi-core and cloud systems.

Manage datasets and models directly from a powerful CLI, providing full control over your workflow without leaving the terminal.

Run multiple ML projects on the same machine without conflicts, ensuring that dependencies are isolated for seamless development.

Organize datasets efficiently by metadata, versions, variants, dependencies, and lifecycles, enabling easy tracking and reproducibility.

Access and manage pretrained models with versioning and adaptations, enabling easy integration into your projects and reducing time spent on training.

Use prebuilt templates based on the Delta framework for faster setup, allowing you to quickly begin experiments with minimal configuration.

Browse datasets and models shared by the community in the Nebula registry, ensuring access to high-quality resources for your projects.

Host your own Nebula registry for secure and confidential work, keeping sensitive data and models private while maintaining efficient access management.