Data Science Project| Predicting Loan Approvals Using Decision Tree & Random Forest

🚀 Welcome to this End-to-End Machine Learning Project!

In this video, we dive deep into building a Loan Approval Prediction Model using Decision Tree and Random Forest algorithms. If you're learning machine learning or preparing for data science interviews, this walkthrough is a great place to start!

✅ What You'll Learn:
Data cleaning & preprocessing

Handling missing values

Encoding categorical variables

Feature selection

Model building with Decision Tree and Random Forest

Model evaluation and accuracy metrics

How to explain your ML project in interviews

📊 Dataset Info:
The dataset contains 600 entries with features such as Gender, Married status, Dependents, Education, Income, LoanAmount, Credit History, Property Area, and more. The goal is to predict Loan_Status — whether a loan will be approved or not.

Github link:- github.com/Rajeev-Mishraa/Loan-Approval-Prediction…

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