There are 2 repositories under distributed-ml topic.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
đź”® SuperDuperDB: Bring AI to your database! Build, deploy and manage any AI application directly with your existing data infrastructure, without moving your data. Including streaming inference, scalable model training and vector search.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
deploy ML Infrastructure and MLOps tooling anywhere quickly and with best practices with a single command
Nerlnet is a framework for research and development of distributed machine learning models on IoT
A fully adaptive, zero-tuning parameter manager that enables efficient distributed machine learning training
Repository that contains the code for the paper titled, 'Unifying Distillation with Personalization in Federated Learning'.
Akka-based framework for distributed ML on fog
Caffe: a fast open framework for deep learning. Caffe-pslite: run deep learning in a cluster with ps-lite (including SSP model)