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What are best practices for XGBoost & Gradient Boosting

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Answer

When working with XGBoost & Gradient Boosting, start with a clear goal, test on real data early, keep the approach as simple as possible at first, and follow established practices from the AI community rather than guessing.
Real-world example A data science competition winner often uses XGBoost because of its strong performance and speed on structured, tabular data.

Common follow-ups: What is Predictive Modeling, How is XGBoost & Gradient Boosting evaluated in practice, What tools are commonly used for XGBoost & Gradient Boosting