Overview

NimbusML provides state-of-the-art ML algorithms, transforms and components, aiming to make them useful for all developers, data scientists, and information workers and helpful in all products, services and devices. The components are authored by the team members, as well as numerous contributors from MSR, CISL, Bing and other teams at Microsoft.

Getting Started

NimbusML is a Python module that provides experimental Python bindings for ML.NET. It provides battle-tested state-of-the-art ML algorithms, transforms and components, aiming to make them useful for all developers, data scientists, and information workers and helpful in all products, services and devices. The components are authored by the team members, as well as numerous contributors from MSR, CISL, Bing and other teams at Microsoft.

nimbusml is interoperable with scikit-learn estimators and transforms, while adding a suite of highly optimized algorithms written in C++ and C# for speed and performance. NimbusML trainers and transforms support the following data structures for the fit() and transform() methods:

  • numpy.ndarray

  • scipy.sparse_cst

  • pandas.DataFrame.

In addition, NimbusML also supports streaming from files without loading the dataset into memory, which allows training on data significantly exceeding memory using FileDataStream.

With FileDataStream, NimbusML is able to handle up to billion features and billions of training examples for select algorithms.

NimbusML can be easily used for the following problems:

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For more details, please refer to the tutorial section.

Used by

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