How to Build First CC Fraud Model using CatBoost

A first submission to Kaggle’s IEEE-CIS Fraud Detection competition

Last week I mentioned I would be working through the new IEEE-CIS Fraud Detection Kaggle Competition as a mechanism for exploring some Data Science concepts. The first video walked you through setting up a Python environment and using version control for an ML project.

This week, I have a new video that dives into the data and builds the first model using the Gradient Boosting library, Catboost. Check it out below!

Originally published at https://blog.zakjost.com