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There’s a new game in town! The new boosted model called CatBoost is making waves! Full disclosure, I am a huge fan of XGBoost. So let’s compare these two boosted models and see what they’re made of. Welcome to 5 Minutes for Data Science! 5 minutes because I talk waaay too much.

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There’s a new game in town! The new boosted model called CatBoost is making waves!

Full disclosure, I am a huge fan of XGBoost. I have been using it since 2014, practically since Tianqi Chen released his research project into the public domain. It was my secret weapon, few knew about it then, and it worked great in R, was fast, etc. But CatBoost caught my eye ( and in a good way. It’s brochure states more accurate, faster, and less memory than XGBoost? Wow, caught both of my eyes!

So, welcome to 5 minutes for data science – My name is Manuel Amunategui, Your host of the ViralML show – 5 minutes because I talk way too much.

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I got some of my best scores on Kaggle using it! At one point, I was ranked 185th and I thank XGBoost ( lot’s of others thanked XGBoost too.People don’t laugh anymore We still thank it today – it’s integrated all over the place – scikit-learn, cloud providers, I use it every day for customers in GCP as it is now compatible with Cloud ML, so you can model terabytes of data using it.

GCP Built-in XGBoost algorithm

Scikit-Learn API
Scikit-Learn Wrapper interface for XGBoost