Lending Club Loan data analysis

Explanatory Data Analysis and ML model building using Apache Spark and PySpark

Building Classification & Prediction model to classify the Loan applicant request as approved or rejected and then predict the Interest rate for Loan Approval.

P2P

📘 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

Case study to identify risky loan applicants and understand factors that contribute to a loan default.

LendingClub API interface

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.

Prediction Of Loan Repayment using Sequential Neural Networks on Lending Club Dataset.

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.

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.

Minimizing bad-risk loan approvals by accurately predicting the applicant's credit risk to reduce financial losses and improve the decision-making process.

Open de Essay First. My first step into Data Science: Data from Lending Club. I used R, Colab and PowerBi. Documentation in Spanish.

A Python wrapper for the Lending Club API.