Part 1: Project Overview & Architecture

1. Project Overview

1.1 Welcome & Introduction

When you apply for a credit card, banks don’t manually read your paper application anymore. Instead, they use smart algorithms called Machine Learning models to make the decision instantly.

In this handbook, we will build a complete Credit Card Approval System from scratch.

The goal of this project is to build a machine learning model that takes applicant demographics (like income, age, employment duration, and education) and predicts whether they should be approved or rejected.

1.2 System Architecture Flow Diagram

Here is how data flows through the application:

graph TD
    A[1. application_record.csv & credit_record.csv] --> B[2. ID-based Join & Label Engineering]
    B --> C[3. Jupyter Notebook EDA & Data Preparation]
    C --> D[4. Balanced Random Forest Training]
    D --> E[5. Serialized Model card_model.joblib]
    E --> F[6. Flask Web Server app.py]
    F --> G[7. HTML/CSS/JS Frontend UI Form]