Please provide the below content related to the project notebook and report.
1 Project Notebook
Please provide the following regarding the project notebook (Note: Python 3.8+/sklearn 0.22+/ONNX 1.7+):
• A Scikit-Learn based Pipeline for training with the provided data in csv format - model research/fit development.
• A ONNX based Model for testing with a runtime session in onnx format - model deployment/edge inference.
2 Project Report
Please provide the following regarding the project report (Note: Can be inline with the Project Notebook):
• Abstract - Research summary, findings, and next steps.
• Overview - Problem statement, relevant literature, proposed methodology. • Data Processing - Pipeline details, data issues, assumptions/adjustments.
• Data Analysis - Summary statistics, visualization, feature extraction.
• Model Training - Feature engineering, evaluation metrics, model selection.
• Model Validation - Testing results, performance criteria, biases/risks.
• Conclusion - Positive/Negative results, recommendations, caveats/cautions.
• Data Sources - Links, downloads, access information.
• Source Code - Listings, documentation, dependencies (open-source).
• Bibliography - Reference citations (Chicago style - AMS/AIP or ACM/IEEE).
Prof. Panchal:
