What to Build:

generative or predictive model trained on the given dataset to sort the data.

What to Submit:

• Code Files:

  • Complete project code in a structured folder.
  • Include:
    • Scripts (.py) or Jupyter Notebooks (.ipynb).
    • A requirements.txt file for dependencies.
    • A README.md file with setup instructions.

• Predictive Model (optional):

  • Submit the trained model file in the appropriate format:
  • Choose one of the following formats.
    • .pkl (scikit-learn or similar libraries).
    • .h5 (TensorFlow/Keras).
    • .pt (PyTorch).
  • Include instructions for loading and testing the model.

• Outputs/Results:

  •  Results:
    • Submit a .csv file 
  •  Response Predictions (optional):
    • Submit a .csv file Report/Documentation:
  • Submit a breif PDF  report:
    • Methodology (segmentation and predictive modeling).
    • Performance metrics (e.g., F1-score, confusion matrix).
    • Business insights and recommendations.

• Visualizations: (optional)

  • Key plots (e.g., segmentation visualizations, feature importance, ROC curve).
  • Can be submitted as separate image files (.png, .jpg) or embedded in the report.