It's a classification model that predict whether an individual will suffer from autism in future or not

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

Using the imbalanced-learn and Scikit-learn libraries to build and evaluate machine learning models.

peer-to-peer lending, use techniques to train and evaluate Machine Learning models with imbalanced classes to identify the worthy

Supervised Machine Learning

Data preparation, Statistical reasoning, Machine Learning

Credit Risk Analysis utilizing imbalanced classification machine learning models

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

Uses several machine learning models to predict credit risk.