Using QPython for Analytics and Data Science Teams

Harnessing the full potential of your data is critical to driving impactful insights and innovation. QPython, Quantexa’s Python SDK, empowers data scientists to build cutting-edge ML and AI models by leveraging Quantexa’s robust Network features and Knowledge Graphs.
In this guide, we’ll walk you through extracting and flattening documents and entities from Parquet files, re-ingesting model outputs into Quantexa, and implementing QPython in your workflows. Whether you're new to QPython or looking to refine your expertise, this article will equip you with the knowledge to deploy it effectively and elevate your data science initiatives.
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Comments
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Hello,
Would I be able to develop logit models for transaction monitoring in Q python and implement them in Quantexa ?
Cheers,
Nils
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Hey @Nilkj !
I'd recommend posting a question over on our Platform Topic, and one of our Support Engineers will then help out with your query!
Dan Pryer - Senior Engineer
R&D - Decision Systems / Detection Packs
Did my reply answer your question? Then why not mark it as having answered in the bottom right corner of my post! 😁
0
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