771: Gradient Boosting: XGBoost, LightGBM and CatBoost, with Kirill Eremenko
Super Data Science: ML & AI Podcast with Jon Krohn
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Deep Learning vs. Gradient Boosting and Ensembling
The chapter explores the differences between deep learning and gradient boosting for different data types, highlighting deep learning's effectiveness for large data inputs and gradient boosting's suitability for tabular data. It also covers ensembling methods, emphasizing the use of weak learners like decision trees, and discusses predicting customer spending behavior with decision trees based on variables like income and age.
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