CatBoost tutorials
Basic
It's better to start CatBoost exploring from this basic tutorials.
Python
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Python Tutorial
- This tutorial shows some base cases of using CatBoost, such as model training, cross-validation and predicting, as well as some useful features like early stopping, snapshot support, feature importances and parameters tuning.
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Python Tutorial with task
- There are 17 questions in this tutorial. Try answering all of them, this will help you to learn how to use the library.
R
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R Tutorial
- This tutorial shows how to convert your data to CatBoost Pool, how to train a model and how to make cross validation and parameter tunning.
Command line
Classification
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Classification Tutorial
- Here is an example for CatBoost to solve binary classification and multi-classification problems.
Ranking
Feature selection
Model analysis
Custom loss
Apply model
Tools
Competition examples
Events
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PyData Moscow tutorial
- Tutorial from PyData Moscow, October 13, 2018.
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PyData NYC tutorial
- Tutorial from PyData New York, October 19, 2018.
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PyData LA tutorial
- Tutorial from PyData Los Angeles, October 21, 2018.
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PyData Moscow tutorial
- Tutorial from PyData Moscow, April 27, 2019.
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PyData London tutorial
- Tutorial from PyData London, June 15, 2019.
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PyData Boston tutorial
- Tutorial from PyData Boston, April 30, 2019.
Tutorials in Russian
- Find tutorials in Russian on the separate page.