Amazon SageMaker Solution for explaining credit decisions.
Business Intelligence( BI) & Tableau
Machine Learning
This project about deployment machine learning model Loan Approval Prediction using Streamlit
Loan Prediction
Predicting if Loan Would be granted or no , based on some given factors using Python
We build a Tensorflow neural network model to predict loan level prepayment using data from Fannie Mae
Data Analysis and prediction on Kaggle dataset: House Loan Data Analysis-Deep Learning
About This project focuses on performing EDA on a real-world Loan Prediction dataset. It includes data cleaning, summary statistics, and visualizations to uncover trends related to income, loan amount, credit history, and more.
#machine Learning #Logistic Regression #Loan Prediction
Machine Learning Based Loan Approval Automation: Enhancing Efficiency, Accuracy, and Fairness in Credit Decision Making
A machine learning API built with Python, FastAPI, and Scikit-learn to predict borrower repayment risk based on historical payment data. A FinTech risk assessment system that uses a Random Forest model to predict a borrower's future repayment behavior and serves the prediction via a REST API.
Machine Learning-Based Loan Approval Automation: Enhancing Efficiency, Accuracy, and Fairness in Credit Decision-Making
This project applies machine learning to predict house prices, loan approvals, and stock market trends. Using datasets from real estate, financial lending, and stock markets, it builds predictive models for data-driven decision-making.
This is a machine learning project developed by Monali and Jayash Bhardwaj as a final group project for our internship at Hoping Minds. The project aims to predict loan approval based on various applicant features using a Random Forest Classifier.
Generating a detailed analysis in case a person is not eligible for a loan using Large Language Model and Loan-default-prediction model deployed as API
SmartSetu-AI is a Streamlit-based dashboard for automated vendor credit and risk scoring.
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