Could Someone Give Me Guidance on Integrating KDB+/q with Machine Learning?

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https://learninghub.kx.com/forums/topic/could-someone-give-me-guidance-on-integrating-kdb-q-with-machine-learning

Hello there,

Right now I am working on a project where I need to integrate KDB+/q with machine learning models. Specifically, I am interested in using KDB+/q to preprocess data, train models, and serve predictions.

I have already explored some basic examples and tutorials, but I am looking for more in-depth resources or best practices for integrating KDB+/q with popular machine learning frameworks such as TensorFlow or PyTorch.

Also, I am curious about any experiences or tips that the community can share regarding performance optimization when using KDB+/q with large-scale machine learning models and datasets.

For reference I have taken help from this: https://stackoverflow.com/questions/47354958/connect-api-to-kdb-databaseinfo

If anyone has worked on similar projects or has any resources to recommend, I would greatly appreciate your insights.

Thankyou in advance.

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There are a lot of resources here: https://code.kx.com/q/ml/


Note: These show use of embedPy which is still usable but is not being actively updated. These can be however be migrated to use the current Python interface PyKX which includes notes on upgrading from embedPy.


Related to the question to you linked to you may be interested in this Websocket example interfacing with coinapi.io: