Portfolio of projects
Loan default prediction is one of the most critical and crucial problem faced by financial institutions and organizations as it has a noteworthy effect on the profitability of these institutions. In recent years, there is a tremendous increase in the volume of non – performing loans which results in a jeopardizing effect on the growth of these i…
Loan Defaulter's Prediction using Statistical Analysis
A project to compare machine learning algorithms for a loan default dataset using MATLAB.
Clustering bank loan customers using KMeans clustering and predicting their loan statuses using XGBClassifier. The prediction model is explained with SHAP values.
2nd Place Overall in Tartan Data Science Cup S-17
The project entails building a model that predicts if someone who seeks a loan might be a defaulter or a non-defaulter. We have several independent variables like, checking account balance, credit history, purpose, loan amount etc. Ensemble Models such as Bagging, AdaBoosting, GradientBoost, XGBoost, Random Forest etc will be used for the modelling
Decision_Trees_and_Random_Forests
learning project about comparing various models for loan acceptance predictance and improving accuracy with the Decision Tree classifier model
Analyzed credit loan data from Kaggle. with 132 variables and 300000+ records. The aim is to find significant factors that contribute to the loan default
In this project, based on the historical data of customers, who has applied for loans, we will identify whether loan should be approved or not. This dataset belongs to Lending Club.
Goal is to determine whether client (Lending Club) should invest in P2P loans.
Loan Default Prediction Dataset from Kaggle and default prediction using machine learning techniques
Predicting Loan Defaulters using various Classification Algorithms using Python (Numpy, Pandas, Sklearn, Matplotlib, Seabon)
We compare prediction accuracy of loan deferral for a particular customer using 4 different unsupervised classification techniques
My projects and practices on various segments of machine learning and deep learning.
The repo contains a loan prediction model implemented in python using the SVM algorithm. The model predicts loan approval based on historical loan application data
A model that predicts whether an applicant will be able to repay a loan using historical data
Loan-Default-Prediction
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