Practical Data Science using Python - Decision Tree - Learning Steps

The video tutorial explains decision trees, focusing on their structure, features, and advantages. It covers the process of building decision trees, including selecting the best attributes and conditions using metrics like Gini impurity and entropy. Key concepts such as nodes, splitting, and pruning are discussed, highlighting how decision trees handle data and avoid overfitting. The tutorial also emphasizes the simplicity and interpretability of decision trees, making them a valuable tool in data analysis.

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