Summary

Your journey through XGBoost has officially begun! You started this chapter by learning the fundamentals of data wrangling and pandas, essential skills for all machine learning practitioners, with a focus on correcting null values. Next, you learned how to build machine learning models in scikit-learn by comparing linear regression with XGBoost. Then, you prepared a dataset for classification and compared logistic regression with XGBoost. In both cases, XGBoost was the clear winner.

Congratulations on building your first XGBoost models! Your initiation into data wrangling and machine learning using the pandas, NumPy, and scikit-learn libraries is complete.

In Chapter 2, Decision Trees in Depth, you will improve your machine learning skills by building decision trees, the base learners of XGBoost machine learning models, and fine-tuning hyperparameters to improve results.