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Machine Learningintermediate

2 Stage Loan Approval & Valuation System

This project is a real-world, end-to-end Machine Learning application that simulates how financial institutions evaluate loan applications. It uses a two-stage modeling approach where the first model decides whether a loan should be approved or rejected, and the second model predicts the optimal loan amount for approved applicants. The project covers the full ML lifecycle from dataset understanding and experimentation in Jupyter Notebook to modular Python code, configuration management using YAML, and deployment on Streamlit Cloud.

13 lectures

What You Will Learn

How real banks evaluate loan applications using financial and credit features
Designing a two-stage ML pipeline (Classification → Regression)
Building robust preprocessing pipelines using ColumnTransformer and Pipeline
Hyperparameter tuning using GridSearchCV and model evaluation with business context
Writing modular, production-ready ML code with configuration files
Deploying an ML application using Streamlit Cloud with a user-friendly UI

System Architecture

2 Stage Loan Approval & Valuation System Architecture Diagram

High-level architecture overview of the 2 Stage Loan Approval & Valuation System .

What You'll Build

  • A Two-Stage Machine Learning Engine
  • An Automated Preprocessing Pipeline
  • A Configuration-Driven Framework
  • A Modular Python Package
  • An Interactive Streamlit Dashboard
2 Stage Loan Approval & Valuation System
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