Abstract
In this chapter, we explore the concept of decision trees, prioritizing accessibility by
minimizing abstract mathematical theories. We examine a concrete numerical example using a
small dataset to predict the suitability of playing tennis based on weather conditions, guiding
readers through the process step-by-step. Moreover, we provide sample codes and compare
them with the decision tree classification model found in the scikit-learn library. Upon
completing this chapter, readers will have gained a comprehensive understanding of the inner
workings of decision tree machine learning, the relationship between the underlying principles,
and the implementation and performance of the algorithm, preparing them to apply their
knowledge to practical scenarios.