Deep Neural Network as SQL+Python

Netanel Stern Netanel Stern
Language: Hebrew
The presentation was given on 2025.01.19 at Deep Neural Network as SQL+Python.

Short Outline: DNN with SQL + Python using Built-in SQL Functions

  1. Data Preprocessing in SQL:
    • Use SQL's built-in functions (SUM(), AVG(), ROUND(), etc.) to perform calculations directly in the database.
  2. Fetch Processed Data in Python:
    • Execute SQL queries with processed results using libraries like pandas and sqlalchemy.
  3. Feature Preparation in Python:
    • Split the SQL output into features (X) and targets (y), normalize data, and handle missing values.
  4. Build and Train DNN Model:
    • Create a neural network with libraries like TensorFlow/PyTorch.
    • Train using preprocessed features as input.
  5. Store Results in SQL:
    • Save predictions or results back into the database for further analysis.