Sostieni JuniperML

Juniper: Dynamic Neural Network Research Platform

Juniper is an AI/ML research platform for investigating dynamic neural network architectures and novel learning paradigms. The project emphasizes ground-up implementations from primary literature, enabling a more transparent exploration of fundamental algorithms.

Juniper ML

juniper-ml is the public face of the Juniper platform on PyPI. It is the meta-distribution that aggregates the platform's services (juniper-canopy, juniper-cascor, juniper-data), client libraries (juniper-data-client, juniper-cascor-client), distributed worker (juniper-cascor-worker), and shared tooling (juniper-ci-tools, juniper-doc-tools, juniper-observability) behind a single installation entry point. The package additionally serves as the version anchor for cross-component compatibility, the home of the platform-level documentation index, and the host repository for independently tagged sibling packages such as juniper-observability and juniper-doc-tools. External callers who want to interact with Juniper services from their own Python code should start here.

Package Distribution

juniper-ml is published on PyPI as juniper-ml. It provides a single installation entry point for the platform's client stack:

pip install juniper-ml[all]

Published components — juniper-canopy, juniper-cascor, juniper-data, juniper-data-client, juniper-cascor-client, juniper-cascor-worker, juniper-ci-tools, juniper-doc-tools, and juniper-observability — remain installable in isolation for callers that require finer control over their dependency surface.