A Deep Learning analysis to predict success of charity campaigns

Machine learning models for predicting credit risk in LendingClub dataset.

Supervised Machine Learning and Credit Risk

Credit Risk Analysis utilizing imbalanced classification machine learning models

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

Credit Risk Analysis utilizing imbalanced classification machine learning models

Uses several machine learning models to predict credit risk.

Supervised scikit-learn machine learning models using several sampling techniques.

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

Data preparation, statistical reasoning and machine learning are used to solve an unbalanced classification problem. Different techniques are employed to train and evaluate models with unbalanced classes.

The purpose of this study is to recommend whether PureLending should use machine learning to predict credit risk. Several machine learning models are built employing different techniques, then they are compared and analyzed to provide the recommendation.

Supervised Machine Learning