SimpleML

Machine learning that just works, for effortless production applications.

It was inspired by common patterns I found myself developing over and over again for new modeling projects. At the core, it is designed to be minimally intrusive and provide a clean abstraction for the most common workflows. Each supported framework details methods to save, version, and subsequently load objects to easily move from training to production.

SimpleML is designed for data scientists comfortable writing code. Please refer to the enterprise version (Enterprise) for details on the extended offering. The enterprise version contains a non-technical interface to SimpleML as well as additional components to streamline the rest of the machine learning product workflow.

What It Is

SimpleML is a framework that manages the persistence and tracking of machine learning objects.

What It Is NOT

As an abstracted persistence layer, SimpleML does not define any native predictive algorithms. It wraps existing ones with convenience methods to save, load, and otherwise manage modeling work.

Prototypical Use Cases:

  • deploy locally trained models to remote servers
  • define model configs to be trained on a remote server
  • experiment with hundreds of different config combinations and track performance

Why use SimpleML over a SAS cloud solution?

  • Avoid vendor lockin - fully open source codebase, compatible with any cloud infrastructure and algorithm backend.
  • Drop in replacement for most workflows
  • Can still deploy your models on-prem without changing your application

Supported Frameworks

SimpleML can easily be extended to support almost any modeling framework. These are the ones that have been developed already:

  Supervised Unsupervised Reinforcement Learning
Scikit-Learn X    
Keras X    
PyTorch      
Tensorflow      
Theano      
AI-Gym      
Caffe      
CNTK      
MXNet      

Source

You can access the source code at: https://github.com/eyadgaran/SimpleML

Contributing

See guidelines here: Contributing

Support

SimpleML core is open source and is powered by generous donations. Please donate if you find it contributing to your projects. Technical support and contract opportunities are also available - contact the author, Elisha Yadgaran, for details.

Ready to get started? Check out the Quickstart guide.