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.
Copy, paste... done.