An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
bring keras-models to production with tensorflow-serving and nodejs + docker 🍕
Deploy machine learning projects developed in Python, to Kubernetes. Accelerated MLOps 🚀
Ml Model Ci
MLModelCI is a complete MLOps platform for managing, converting, profiling, and deploying MLaaS (Machine Learning-as-a-Service), bridging the gap between current ML training and serving systems.
DELTA is a deep learning based natural language and speech processing platform.
Deploy DL/ ML inference pipelines with minimal extra code.
AsyncIO serving for data science models
A flexible, high-performance serving system for machine learning models
A scalable inference server for models optimized with OpenVINO™
A flexible, high-performance carrier for machine learning models（『飞桨』服务化部署框架）
The open big data serving engine. https://vespa.ai
Deep Learning In Production
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
Exposes a serialized machine learning model through a HTTP API.
Exploratory Video Analytics System
A Hybrid Serving & Analytical Processing Database.
TensorFlow Serving ARM - A project for cross-compiling TensorFlow Serving targeting popular ARM cores
Serve your fastText models for text classification and word vectors