CatBoost is well covered with educational materials for both novice and advanced machine learners and data scientists.
- Video tutorial
This tutorial gives a short introduction to CatBoost and showcases its' functionality in Jupyter Notebook.
- Getting started tutorials
- Perform the following steps to use them:
Download the tutorials using one of the following methods:
- Click the Download button on the github page
- Clone the whole repository using the following command:
git clone https://github.com/catboost/tutorials
Run Jupyter Notebook in the directory with the required ipynb file.
- CatBoost on GPU
- This tutorial shows how to run CatBoost on GPU with Google Colaboratory.
- Tutorials in the CatBoost repository
The CatBoost repository contains several tutorials on various topics, including but no limited to:
- how to apply the model
- how to use custom losses
- how to train a ranking model
- how to perform hyperparameter search
- Coursera tutorials
Coursera provides several lectures and a programming assignment as a part of the How to Win a Data Science Competition: Learn from Top Kagglersspecialization.
The assignment helps to explore all basic functions of the CatBoost Python package.
The results can be submitted to Coursera for further validation.
- Applying CatBoost models in ClickHouse
The ClickHouse documentation contains a tutorial on applying a CatBoost model in ClickHouse.