Practical Data Science using Python - Decision Tree - Model Concept

The video tutorial introduces classification algorithms, focusing on decision trees. It explains how decision trees work, including optimization techniques using Gini index and Entropy. Examples of classification problems, such as email spam detection and credit card fraud, are discussed. The tutorial covers different types of classification problems, including binary, multiclass, and multi-label. Popular classification algorithms like decision trees, random forests, naive bayes, KNN, and SVM are highlighted. The session concludes with a detailed explanation of decision trees, their structure, and how they learn from data.

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