Machine Learning - End to End Data Science Projects

A Classification Problem which predicts if a loan will get approved or not.

Predicts a chance of loan repayment based on historical data

Predicting Loan State with SVM method, preprocessing and feature selction

Predict if your loan will be accepted or not. This happens by using a labeled data for applicants who applied for a loan before, analyzing these data and using some classification models on it.

A demo pipeline of using Redis as an online feature store with Feast for orchestration and Ray for training and model serving

This project automates bank credit risk assessment using AI and machine learning models to predict loan defaults. It streamlines the credit process with predictive analytics, model evaluation, explainability (SHAP), and deployment readiness.

An example of using Redis + RedisAI for a microservice that predicts consumer loan probabilities using Redis as a feature and model store and RedisAI as an inference server.

This repository contains a machine learning-based predictive model for automating loan eligibility assessments. Using features such as demographic details, loan information, and credit history, the model predicts whether a loan should be approved or denied.

Loan Prediction using Machine Learning algorithms

Loan eligibility prediction in Lasiandra Finance Inc. (LFI) using SAS studio.

What's up This project was mainly training my self on training ML models 🤖 and also to train on doing EDA 📜 to get the acceptance of the loan.

Code developed for my AC classes, FEUP - MEIC (2021/22)

I’d be walking us through Loan prediction using some selected Machine Learning Algorithms.

This repo is for derived from a competition from analytics vidhya for predicting loan using the data given.

Loan Prediction using Machine Learning

This app utilizes deep learning to predict the loan status of an applicant, whether it's "Fully Paid" or "Charged Off".

This a practice project for Classification model with different models like Logistic Regression, Decision Tree Classifier, Random Forest Classifier and Xgboost Classifier. At the end, Logistic Regression gave the best result.

An End-to-End production ready application for predict whether the loan will approve or not. assesses the likelihood of approving a loan. 📊💰 It involves collecting and processing data on applicants, training a model to predict loan approval, and creating a system for real-time predictions. 🤖