This repository contains the solution for the Vi Data Scientist Home Assignment, aimed at predicting members most likely to purchase a personal training package.
- ViLabs_OfirSuranyi.ipynb: Jupyter notebook with detailed analysis, data preprocessing, and model training.
- Inference.py: Python script for model inference on new data.
- Model.pkl: Serialized trained model for predictions.
- requirements.txt: List of Python libraries required to run the notebook and scripts.
Data is accessible through ViLabs or a specified path, including events data and subscribers data.
- Install required libraries using pip install -r requirements.txt.
- Download the data from ViLabs or use the provided path.
- Follow the notebook ViLabs_OfirSuranyi.ipynb for analysis and model development.
- Use Inference.py and Model.pkl for predictions on new data.