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Introduces decision trees for classification, covering entropy, split quality, Gini index, advantages, disadvantages, and the random forest classifier.
Explores encapsulation and abstraction in object-oriented programming through a Tic-Tac-Toe case study, highlighting the benefits of data encapsulation and controlled access.
Explores overfitting, regularization, and cross-validation in machine learning, emphasizing the importance of model complexity and different cross-validation methods.
