The Real Python Podcast Improving Classification Models With XGBoost
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Aug 25, 2023 Author and Python trainer Matt Harrison discusses his new book on improving classification models with XGBoost. He emphasizes the importance of exploratory data analysis and provides tools to explain models to stakeholders. The podcast also covers the popularity of XGBoost, the concept of prediction in data science, and the application of XGBoost in classification models.
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Book Born From Trainer Frustration
- Matt Harrison wrote the book to scratch his own itch after corporate training showed gaps in existing XGBoost resources.
- He built a more actionable, hands-on guide because available material lacked the practical depth he wanted.
What Tabular Prediction Really Means
- Tabular prediction means supervised learning on structured rows and columns like spreadsheets or databases.
- It contrasts with unstructured data such as images, audio, or video which lack a fixed tabular shape.
Prepare Your Environment First
- Know Python and basic tooling like Jupyter and pandas before using the book's XGBoost examples.
- Use Jupyter for interactive exploration but handle preprocessing and cleaning outside the book's focus.