Oc_p7

Overview

The project is based on the Kaggle competition using Home Credit data to develop a machine learning model for predicting client default. The goal is to support the decision of whether or not to grant a loan to a client. The model is trained and then made available through an API. Additionally, an interactive dashboard is developed for relationship managers to explain credit approval decisions. The dashboard calls the API to retrieve the client's score.

Features

• Machine learning model for predicting client default
• API deployment of the machine learning model
• Interactive dashboard for relationship managers to explain credit approval decisions

Summary

This project utilizes Kaggle's Home Credit data to develop a machine learning model for predicting client default. The model is trained and deployed as an API, which can be accessed by an interactive dashboard. The dashboard is designed to help relationship managers explain credit approval decisions. The project also provides instructions for deploying the model and dashboard on Heroku.