Learn CATBOOST with Real Code Examples

Learn Python and scikit-learn basics

Understand decision trees and gradient boosting

Practice CatBoost on classification and regression tasks

Explore hyperparameter tuning and categorical feature handling

Integrate into ML pipelines and production workflows

Week 1: train simple classifier/regressor

Week 2: handle categorical features and cross-validation

Week 3: ranking tasks and GPU training

Week 4: custom loss functions and distributed learning

Week 5: deployment and integration into pipelines

How does CatBoost handle categorical features?

Explain ordered boosting and its benefits

Difference between CatBoost, LightGBM, and XGBoost?

How to prevent overfitting in CatBoost?

How does CatBoost handle missing values?

CatBoostClassifier() = classification model

CatBoostRegressor() = regression model

Pool() = dataset object

fit() = train model with parameters

predict() = generate predictions

Hands-On Gradient Boosting with CatBoost

Mastering Machine Learning with CatBoost

Advanced Boosting Techniques in Python

Tabular ML with CatBoost and LightGBM

Applied Machine Learning with CatBoost

CatBoost official tutorials

Kaggle CatBoost example notebooks

Medium blogs on CatBoost tips

YouTube tutorials on gradient boosting

Hands-on tabular ML courses using CatBoost

https://catboost.ai/docs/

https://github.com/catboost/catboost

CatBoost GitHub

StackOverflow CatBoost tag

Kaggle forums

Reddit ML and Kaggle communities

Blogs and tutorials online

CatBoost GitHub repository

StackOverflow CatBoost tag

Kaggle forums and competitions

Medium and blog tutorials

Yandex CatBoost official discussions