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nimbusml
is a Python module that provides Python bindings for ML.NET.
nimbusml
aims to enable data science teams that are more familiar with Python
to take advantage of ML.NET's functionality and performance. It provides
battle-tested, state-of-the-art ML algorithms, transforms, and components. 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 fast, highly optimized, and scalable algorithms written
in C++ and C#. 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 with FileDataStream
, which allows training on data
significantly exceeding memory.
With FileDataStream
, nimbusml
is able to handle up to a billion
features and billions of training examples for select algorithms.
For more details, please refer to the documentation: https://docs.microsoft.com/en-us/nimbusml.
nimbusml
contains ML.NET binaries and the .NET Core CLR runtime, as well as
their dependencies. Both ML.NET and .NET Core CLR are made available under the
MIT license. Please refer to the third party notices
for full licensing information for ML.NET and .NET Core CLR.
FAQs
NimbusML
We found that nimbusml demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
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Socket MCP brings real-time security checks to AI-generated code, helping developers catch risky dependencies before they enter the codebase.
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