Decision trees are a tree-based machine learning model used for classification and regression tasks

Decision trees work by making decisions based on feature values

Decision trees are easy to understand and to interpret, so they often used as a baseline model for comparison with more complex models.

Decision trees can handle both categorical and numerical data

Decision trees are prone to overfitting, which means that they can perform well on the training data but not on unseen data

Decision trees can also be used with other models, such as random forests, to improve their performance

Decision trees can be used for tasks such as prediction, product  recommendation, etc.