ML Hosting Solutions

Acumos AI

Acumos AI is a platform and open source framework that makes it easy to build, share, and deploy AI apps. Acumos standardizes the infrastructure stack and components required to run an out-of-the-box general AI environment.

Acumos is a platform which enhances the development, training and deployment of AI models. Its purpose is to scale up the introduction of AI-based software across a wide range of industrial and commercial problems in order to reach a critical mass of applications. In this way, Acumos will drive toward a data-centric process for producing software based upon machine learning as the central paradigm. The platform seeks to empower data scientists to publish more adaptive AI models and shield them from the task of custom development of fully integrated solutions. Ideally, software developers will use Acumos to change the process of software development from a code-writing and editing exercise into a classroom-like code training process in which models will be trained and graded on their ability to successfully analyze datasets that they are fed. Then, the best model can be selected for the job and integrated into a complete application.

Acumos is part of the LF Deep Learning Foundation, an umbrella organization within The Linux Foundation that supports and sustains open source innovation in artificial intelligence, machine learning, and deep learning while striving to make these critical new technologies available to developers and data scientists everywhere.

Item

Value

SBB License

Apache License 2.0

Core Technology

Java

Project URL

https://www.acumos.org/

Source Location

https://gerrit.acumos.org/r/#/admin/projects/

Tag(s)

ML, ML Hosting

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

https://github.com/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

https://github.com/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

https://github.com/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

https://github.com/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

https://github.com/apple/turicreate

Source Location

https://github.com/apple/turicreate

Tag(s)

ML, ML Framework, ML Hosting

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