Decision Trees are a method in machine learning for making predictions by splitting data into branches based on feature values. They're particularly useful for tasks like text classification, as shown in videos about AI techniques and real-world applications. Understanding how Decision Trees work, along with concepts like random forests, can empower individuals to build effective predictive models.
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