Decision Trees: From Intuition to Implementation

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This lecture series explores decision trees, starting with their fundamentals, including origins and applications in data analysis. It delves into the components such as nodes, branches, and leaves, and examines algorithmic frameworks like ID3 and CART, including splitting and pruning strategies. Advantages and limitations are addressed alongside mitigation techniques. Practical implementation in Python using libraries like scikit-learn is demonstrated, complemented by real-world examples in...