naive-random-oversampler

Testing 6 different machine learning models to determine which is best at predicting credit risk.

Supervised Machine Learning and Credit Risk

The purpose of this analysis was to create a supervised machine learning model that could accurately predict credit risk using python's sklearn library.

This repo is about Machine Learning and Classification

using machine learning to assess credit risk

Established a supervised machine learning model trained and tested on credit risk data through a variety of methods to establish credit risk based on a number of factor

Supervised Machine Learning Project

Uses several machine learning models to predict credit risk.

In this project, I will use credit risk models to assess the credit risk using peer-to-peer lending. Algorithms such as SMOTE, Naive Random Sampling, etc.

Determine supervised machine learning model that can accurately predict credit risk using python's sklearn library. Python, Pandas, imbalanced-learn, skikit-learn

Predicts credit risk of individuals based on information within their application utilizing supervised machine learning models