Uses several machine learning models to predict credit risk.

For this analysis, we used computational linguistics and biometrics to systematically identify the trend using various news articles and closing prices using the "CoinGecko CSV & Crypto News API"!

Supervised Machine Learning and Credit Risk

Build and evaluate several machine learning algorithms to predict credit risk

Resampling exercise to predict accuracy, precision, and sensitivity in credit-loan risk

Extract data provided by lending club, and transform it to be useable by predictive models.

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

Using machine learning to train and evaluate models with unbalanced classes to determine the best models to predict credit risk.

Train and test multiple Machine Learning models to predict risk based on consumer credit profiles.

Built and evaluated variety of supervised machine learning algorithms to predict credit risk.

Analysis of different machine learning models' performance on predicting credit default

Build and evaluate several machine learning algorithms to predict credit risk.

Banking-Dataset-Marketing-Targets

Supervised Machine Learning and Credit Risk

Supervised Machine Learning Project

About Six different techniques are employed to train and evaluate models with unbalanced classes. Algorithms are used to predict credit risk. Performance of these different models is compared and recommendations are suggested based on results. Topics

This repo contains code that looks into LendingClub's membership data and employs ML to see if the model can predict a user's "credit risk" based on lending.

Built and evaluated several machine learning algorithms to predict credit risk.

Supervised Machine Learning