Lending Club Loan data analysis
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Updated
Jul 8, 2019 - Jupyter Notebook
Lending Club Loan data analysis
Building Classification & Prediction model to classify the Loan applicant request as approved or rejected and then predict the Interest rate for Loan Approval.
Explanatory Data Analysis and ML model building using Apache Spark and PySpark
📘 Detailed Exploratory Data Analysis of Lending Club Loan Data
My personal website and blog where I showcase many of my projects and my progress learning data science.
Projects in Data Analysis
LendingClub API interface
Case study to identify risky loan applicants and understand factors that contribute to a loan default.
A R wrapper for the Lending Club API. The package allows you to manage the funds in your investor account and to make trading transactions.
This is our second project at neuefische DS Bootcamp. Silas Mederer (https://github.com/sls-mdr) and me applied different ML models and for credit default prediction of the P2P platform Lending Club.
Prediction Of Loan Repayment using Sequential Neural Networks on Lending Club Dataset.
Master's Project - Classification Models on 'Lending Club' dataset
Southern Data Science Conference Attempt 2020
This repo contains analysis of Lending Club Credit rates and also case study for a client to get a fully funded loan at the lowest credit rate with a desired duration.
Analyzed LendingClub loan data to determine factors associated with loan default. Built machine learning models to predict probability of default.
Mi primer paso en Ciencia de Datos: Default Crediticio LendingClub
Minimizing bad-risk loan approvals by accurately predicting the applicant's credit risk to reduce financial losses and improve the decision-making process.
Loan Default Prediction, Individual Level Loan Data, Machine Learning, Logistic regression, Ridge, LASSO, Gradient Boosting, SVM, Random Forest
This app utilizes deep learning to predict the loan status of an applicant, whether it's "Fully Paid" or "Charged Off".
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