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Learn AI with Python · Lesson

LightGBM and CatBoost

Why LightGBM is faster, histogram-based splitting, CatBoost for categorical features.

Beyond XGBoost

XGBoost is powerful but can be slow on very large datasets. LightGBM and CatBoost are newer gradient boosting libraries that improve speed and handle categorical data more gracefully.

Histogram-Based Splits

LightGBM buckets continuous features into discrete bins (a histogram) before finding splits. This makes split-finding much faster and uses less memory than the exact method.

All lessons in this course

  1. Decision Trees: Theory and Implementation
  2. Random Forests and Bagging
  3. Gradient Boosting: GBM and XGBoost
  4. LightGBM and CatBoost
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