There are 22 repositories under loan-default-prediction topic.
Lending Club Loan data analysis
Modeled the credit risk associated with consumer loans. Performed exploratory data analysis (EDA), preprocessing of continuous and discrete variables using various techniques depending on the feature. Checked for missing values and cleaned the data. Built the probability of default model using Logistic Regression. Visualized all the results. Computed Weight of Evidence and price elasticities.
Prediction of loan defaulter based on more than 5L records using Python, Numpy, Pandas and XGBoost
L&T Financial Services & Analytics Vidhya presents ‘DataScience FinHack’ organised by Analytics Vidhya
Applying machine learning to predict loan charge-offs on LendingClub.com
A Classification Problem which predicts if a loan will get approved or not.
Loan Management System and daily collection Api For Financial institutions.
Loan Default Prediction using PySpark, with jobs scheduled by Apache Airflow and Integration with Spark using Apache Livy
The project provides a complete end-to-end workflow for building a binary classifier in Python to recognize the risk of housing loan default. It includes methods like automated feature engineering for connecting relational databases, comparison of different classifiers on imbalanced data, and hyperparameter tuning using Bayesian optimization.
Predicting the default customers
[Project repo] Improving business with a credit risk model
Capstone Project: Predicting default in P2P lending
Classification problem to predict loan defaulters using Lending Club Dataset
L&T Financial Services & Analytics Vidhya presents ‘DataScience FinHack’ organised by Analytics Vidhya
:blue_book: Detailed Exploratory Data Analysis of Lending Club Loan Data
Streamlit_ML_DL
A repository for the trainee @ codesquad. This repository contains projects that will be executed by trainees to certify that they have master what has been taught to them
Create a model that predicts whether or not a loan will be default using the historical data.
datawhale&科大讯飞举办的学习挑战赛————“车辆贷款违约预测挑战赛” Rank4 方案
The objective of this project is to predict the probability of borrower defaulting on a vehicle loan in the first EMI (Equated Monthly Installments) on the due date.
Tool demonstrating building credit risk models
Business Intelligence( BI) & Tableau
Machine Learning Key Projects
In this data science project, we will predict borrowers chance of defaulting on loans by building a default prediction model.
Lending Club Loan Default Analysis using historic loan applications data.
Supervised Machine Learning model predicting loan default using Logistic Regression.
Loan eligibility prediction in Lasiandra Finance Inc. (LFI) using SAS studio.
This repository contains a starter notebook for the DSN AI Bootcamp Qualification Hackathon
The loan is a core part of every business today. This system will help the bank identify the royal customer for their bank and bank to contribute more to our GDP.
Classification Credit Scoring with Compare Algorithm ML (Ensambled) with Model Evaluation
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.
This app utilizes deep learning to predict the loan status of an applicant, whether it's "Fully Paid" or "Charged Off".