Training a machine learning model

Loan Data Analysis & Prediction | Machine Learning & Data Visualization

I have developed a powerful data analysis and machine learning pipeline to analyze loan data, predict loan amounts, and classify loan approvals using advanced data science techniques.

Key Features & Capabilities:

Comprehensive Data Cleaning & Preprocessing – Handled missing values, removed duplicates, and transformed categorical data for better model performance.

Advanced Data Visualization – Created insightful histograms, pie charts, and count plots to understand loan distribution, risk scores, and approval trends.

Predictive Modeling (Regression) – Built and compared multiple models to predict loan amounts, including:

Linear Regression, Decision Trees, Random Forest, SVR, and KNN

Loan Approval Classification – Developed a machine learning model to classify whether a loan will be approved using:

Logistic Regression, Decision Trees, Random Forest, SVM, KNN, and Naïve Bayes

Model Evaluation & Performance Metrics – Assessed model accuracy using R² Score, Mean Squared Error (MSE), and Classification Accuracy.

Automated Performance Comparison – Visualized model performance with bar charts for easy comparison and selection of the best model.

Business Impact & Use Cases:

Helps financial institutions assess loan risks & predict loan amounts effectively.

Automates loan approval decision-making with machine learning models.

Enhances data-driven strategies for banking, finance, and lending businesses.