|SynapseML Now .NET Compatible|
|Written by Kay Ewbank|
|Thursday, 15 September 2022|
Microsoft has updated SynapseML, its open-source library for creating massively scalable machine learning (ML) pipelines. The update consists of a new set of .NET APIs for massively scalable machine learning as part of the v0.10 release of SynapseML.
SynapseML was originally known as MMLSpark, and it unifies several existing ML frameworks and new Microsoft algorithms in a single, scalable API that’s usable across Python, R, Scala, and Java. It builds on Apache Spark and SparkML, adding deep learning and data science tools to the Spark ecosystem.
SynapseML unifies many different ML learning frameworks with a single API that is scalable, data- and language-agnostic, and that works for batch, streaming, and serving applications. It’s designed to help developers focus on the high-level structure of their data and tasks, not the implementation details and idiosyncrasies of different ML ecosystems and databases.
It integrates Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit, and OpenCV, so through these tools provides highly-scalable predictive and analytical models for a variety of data sources. SynapseML also includes the HTTP on Spark project, meaning users can embed web services into their SparkML models.
The new APIs can be used to author, train, and use any SynapseML model from C#, F#, or other languages in the .NET family with Microsoft's .NET for Apache Spark language bindings.
SynapseML’s .NET bindings are made available in a custom NuGet feed, and are split into several sub-projects including cognitive, deep learning, Light Gradient Boosting Machine, OpenCV and VowpalWabbit (VW). Once installed, you can use SynapseML’s APIs for distributed machine learning on Spark via .NET.
SynapseML 0.10 is available now.
Microsoft Releases Open Source Distributed Machine Learning Library
Microsoft Open Sources Natural Language Processing Tool
Apache Ignite Adds Spark DataFrames Support
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