Capstone Project: Predicting default in P2P lending

2nd Place Overall in Tartan Data Science Cup S-17

Loan Prediction

python_datasets

R exercise to predict probability of default of LendingClub personal loans

Applying machine learning to predict loan charge-offs on LendingClub.com

Machine Learning Key Projects

Predicting loan default using machine learning on Lending Club data from 2007-2011.

This is a one layer neural network that predict whether a loan will be defaulted.

📘 Detailed Exploratory Data Analysis of Lending Club Loan Data

My first attempt with building a SVM model, and optimizing the cost and gamma parameters using the Gaussian Kernel grid search method.

Classification problem to predict loan defaulters using Lending Club Dataset

In this project I applied various classification models such as Logistic Regression, Random Forest and LightGBM to accurately detect and classify consumers who will default the loan. SMOTE technique is used to combat class imbalance and LightGBM is implemented that resulted into the highest accuracy 98.89% and 0.99 F1 Score.

Credit defaulter prediction

A simple sample program that will determine an applicant's eligibility for a loan.