SynapseML: A simple, multilingual, and massively parallel machine learning library

A graphic illustrating that SynapseML unifies a variety of different ML frameworks (including LightGBM, Azure Cognitive Services, Deep Learning, reinforcement learning), scales (including single node, cluster, and serverless + elastic), paradigms (including batch, streaming, and serving), cloud data stores, and languages.

Today, we’re excited to announce the release of SynapseML (previously MMLSpark), an open-source library that simplifies the creation of massively scalable machine learning (ML) pipelines. Building production-ready distributed ML pipelines can be difficult, even for the most seasoned developer. Composing tools from different ecosystems often requires considerable “glue” code, and many frameworks aren’t designed with thousand-machine elastic clusters in mind. SynapseML resolves this challenge by unifying several existing ML frameworks and new Microsoft algorithms in a single,

 

 

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