This project focus on creating a detail analysis and machine learning for decision making predictions based on MSTZ Heloc Dataset huggingface.co.
Heloc lending process improvement is becoming a standard practice for financial institutions. With a precise understanding of the data and given predictions on loan approvals, the bank can improve its decision-making process to minimize risk and streamline approvals. We decided to engage in this project because we believe it's an excellent opportunity and a real-world example to enhance our data science skills with tangible outcomes.
Name | Description | Github Account | |
---|---|---|---|
Santiago Paiz | Software Engineer & Data Scientist | @aaoeclipse | santiago-paiz-7b2a7268 |
Alex "Andru" Andrushevich | Software Engineer & Data Scientist | @QuantGeekDev | alex-andrushevich-5544845a |
- Download MSTZ Heloc Dataset into a data/ folder in the root of the project
- Install python dependencies
python3 -m pip install -r requirements.txt
- Follow the steps in the installation
- setup mlflow with the correct database
mlflow ui --backend-store-uri sqlite:///mlflow.db
- Run the analysis.ipynb