Machine Learning at Microsoft with ML.NET

Matteo Interlandi, Sergiy Matusevych, Saeed Amizadeh, Shauheen Zahirazami, Markus Weimer

Abstract:

Machine Learning is transitioning from an art and science into a technology available to every developer.
In the near future, every application on every platform will incorporate trained models to encode data-based decisions that would be impossible for developers to author. This presents a significant engineering challenge, since currently data science and modeling are largely decoupled from standard software development processes.
This separation makes incorporating machine learning capabilities inside applications unnecessarily costly and difficult, and furthermore discourage developers from embracing ML in first place.
In this paper we introduce ML.NET, a framework developed at Microsoft over the last decade in response to the challenge of making it easy to ship machine learning models in large software applications.

Decision: accept