LukasZahradnik/deep-db-learning
A modular message-passing scheme reflecting the relational model for end-to-end deep learning from databases
This project helps machine learning engineers and data scientists build deep learning models directly from relational databases. It takes a database connection string as input, automatically analyzes the database schema and data, and then converts it into specialized tensor representations. The output is a ready-to-use deep learning model capable of making predictions or classifications based on the complex relationships within the database.
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Use this if you need to apply advanced deep learning techniques to complex, multi-table relational data without extensive manual feature engineering or data flattening.
Not ideal if your data is already in a simple tabular format or if you primarily work with non-relational data sources.
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Language
Python
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Last pushed
May 26, 2025
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