Web App and Random Forest - Loan Approval Prediction

When it comes to deciding whether the applicant’s profile is relevant to be granted with loan or not,banks have to look after many aspects. Predicting loan approval is a common application of machine learning in the financial industry.

A Deep Learning-based Loan Approval Prediction system using Python, TensorFlow, and SQL. Includes data preprocessing, feature engineering, model training with Keras, hyperparameter tuning, and evaluation (accuracy & confusion matrix) to classify applications as approved or rejected

Dataset Predictionl | https://www.kaggle.com/datasets/architsharma01/loan-approval-prediction-dataset

🔍 Predict loan approval and calculate credit risk using a full-stack ML web app with Flask backend, React frontend, and Docker deployment.

Welcome to the Loan Approval Prediction project repository! This project focuses on predicting the approval of loan applications using various machine learning algorithms. By analysing applicant details and financial information, the model aims to assist financial institutions in making data-driven and reliable loan approval decisions.

Predict bank loan approval status using SAS

Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials. AI for Credit Risk Scoring leverages AI to assess financial and behavioral data, predicting creditworthiness and helping lenders make accurate, data-driven decisions to minimize loan defaults.

Loan Approval Prediction System using Ensemble Learning Approaches

Classification pour l'attribution ou non de prêts financiers et prédiction de scores de risque.

A sophisticated, modular machine learning framework for automating loan approval processes, integrating Docker, Jenkins CI/CD, AWS-EC2, and FastAPI for robust, scalable financial decision-making.