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· 2 min read
JJ Brosnan

Base+ images for AI/ML in Python make getting started quicker than ever

The intersection of AI and real-time data is important. PyTorch, TensorFlow, Sci-Kit-Learn, and NLTK are ubiquitous libraries for data science workflows. To service real-time use cases, they pair well with Deephaven, a query engine that brings Python to "streaming dataframes" -- essentially "tables that update".

Uniting these two powerhouses should be easy. The deephaven.learn library was released in December, providing a gather-compute-scatter paradigm to Deephaven's streaming tables, in support of AI integrations.

Today, the team released an upgrade to the deployment options available to AI-motivated users. With a simple curl script, you can now download a Docker image that combines Python, Deephaven, and the AI library of your choice.

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