Build, Deploy and Manage AI/ML Systems
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Updated
Feb 25, 2025 - Python
Build, Deploy and Manage AI/ML Systems
SkyPilot: Run AI and batch jobs on any infra (Kubernetes or 14+ clouds). Get unified execution, cost savings, and high GPU availability via 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.
Efficient Deep Learning Systems course materials (HSE, YSDA)
Aqueduct is no longer being maintained. Aqueduct allows you to run LLM and ML workloads on any cloud infrastructure.
A Collection of GitHub Actions That Facilitate MLOps
🚀 Metadata tracking and UI service for Metaflow!
Utilities for preprocessing text for deep learning with Keras
deploy ML Infrastructure and MLOps tooling anywhere quickly and with best practices with a single command
Run GPU inference and training jobs on serverless infrastructure that scales with you.
MONAI Deploy App SDK offers a framework and associated tools to design, develop and verify AI-driven applications in the healthcare imaging domain.
The official python package for NimbleBox. Exposes all APIs as CLIs and contains modules to make ML 🌸
A standalone inference server for trained Rubix ML estimators.
A tool for training models to Vertex on Google Cloud Platform.
Example ML projects that use the Determined library.
Render Jupyter Notebooks With Metaflow Cards
Kubeflow blog based on fastpages
RFlow - A workflow framework for agile machine learning
The official Python library for Openlayer, the Continuous Model Improvement Platform for AI. 📈
A SageMaker-based ML system solution
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