There are 5 repositories under ml-platform topic.
SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed executionβall with a simple interface.
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
:rocket: Metadata tracking and UI service for Metaflow!
Finetune LLMs on K8s by using Runbooks
MONAI Deploy aims to become the de-facto standard for developing, packaging, testing, deploying and running medical AI applications in clinical production.
The official python package for NimbleBox. Exposes all APIs as CLIs and contains modules to make ML πΈ
MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.
A cloud-agnostic ML Platform that will enable Data Scientists to run multiple experiments, perform hyper parameter optimization, evaluate results and serve models (batch/realtime) while still maintaining a uniform development UX across cloud environments
"1 config, 1 command from Jupyter Notebook to serve Millions of users", Full-stack On-Premises MLOps system for Computer Vision from Data versioning to Model monitoring and drift detection.
A "production-ready" simple project template to quickly start an Artificial Intelligence (AI), Machine Learning (ML) and/or Data Science (DS) project with basic files, branches and directory structure.
Welcome to the Machine Learning Engineering Repository, a comprehensive collection of resources, code, and insights to guide you through the exciting world of machine learning. This repository is designed to provide valuable information, best practices, and hands-on examples for individuals keen on mastering the art and science of machine learning
π₯π₯π₯π₯π§π₯π₯ A Data Platform for Monitoring and Detecting Anomalies in Real-Time.
A SageMaker-based ML system solution
Newron is a data-centric ML platform to easily build, manage, deploy and continuously improve models through data driven development.