ML Hosting Solutions

BentoML

BentoML makes it easy to serve and deploy machine learning models in the cloud.

It is an open source framework for machine learning teams to build cloud-native prediction API services that are ready for production. BentoML supports most popular ML training frameworks and common deployment platforms including major cloud providers and docker/kubernetes.

Documentation on: https://bentoml.readthedocs.io/en/latest/index.html

Item	Value
SBB License	Apache License 2.0
Core Technology	Python
Project URL	http://BentoML.ai
Source Location	bentoml/BentoML
Tag(s)	ML, ML Hosting, Python

RAPIDS

The RAPIDS suite of software libraries gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization, but exposes that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.

RAPIDS also focuses on common data preparation tasks for analytics and data science. This includes a familiar DataFrame API that integrates with a variety of machine learning algorithms for end-to-end pipeline accelerations without paying typical serialization costs–. RAPIDS also includes support for multi-node, multi-GPU deployments, enabling vastly accelerated processing and training on much larger dataset sizes.

Item	Value
SBB License	Apache License 2.0
Core Technology	C++
Project URL	http://rapids.ai/
Source Location	rapidsai/
Tag(s)	ML, ML Hosting, ML Tool

Ray

Ray is a flexible, high-performance distributed execution framework for AI applications. Ray is currently under heavy development. But Ray has already a good start, with good documentation (http://ray.readthedocs.io/en/latest/index.html) and a tutorial. Also Ray is backed by scientific researchers and published papers.

Ray comes with libraries that accelerate deep learning and reinforcement learning development:

• Ray Tune: Hyperparameter Optimization Framework
• Ray RLlib: A Scalable Reinforcement Learning Library

Item	Value
SBB License	Apache License 2.0
Core Technology	Python
Project URL	https://ray-project.github.io/
Source Location	ray-project/ray
Tag(s)	ML, ML Hosting

Streamlit

The fastest way to build custom ML tools. Streamlit lets you create apps for your machine learning projects with deceptively simple Python scripts. It supports hot-reloading, so your app updates live as you edit and save your file. No need to mess with HTTP requests, HTML, JavaScript, etc. All you need is your favorite editor and a browser.

Documentation on: https://streamlit.io/docs/

Item	Value
SBB License	Apache License 2.0
Core Technology	Javascipt, Python
Project URL	https://streamlit.io/
Source Location	streamlit/streamlit
Tag(s)	ML, ML Framework, ML Hosting, ML Tool, Python

Turi

Turi Create simplifies the development of custom machine learning models. Turi is OSS machine learning from Apple.

Turi Create simplifies the development of custom machine learning models. You don’t have to be a machine learning expert to add recommendations, object detection, image classification, image similarity or activity classification to your app.

Item	Value
SBB License	BSD License 2.0 (3-clause, New or Revised) License
Core Technology	Python
Project URL	apple/turicreate
Source Location	apple/turicreate
Tag(s)	ML, ML Framework, ML Hosting

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