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title: DALI ML Challenge | |
emoji: π | |
colorFrom: red | |
colorTo: indigo | |
sdk: gradio | |
sdk_version: 4.27.0 | |
app_file: app.py | |
pinned: false | |
# DALI ML Challenge Deployment | |
Deployment of profit prediction models for the DALI Machine Learning Challenge. I deployed the best performing Logistic Regression, SVM, and XGBoost models I generated. I also generate shapley values for each entry the user inputs to offer greater interpretability to model predictions. | |
## Files: | |
- app.py: App file. A copy of the interface I defined in the profit prediction notebook | |
- Log_Reg.pkl: Serialized copy of the best-performing logistic regression model | |
- SVM.pkl: Serialized copy of the best-performing SVM model | |
- XGB.model: Serialized copy of the best-performing XGB model | |
- Superstore.csv: Dev challenge dataset (needed to generate Shapley values) | |