ML 101: Where Do Decision Trees & Random Forests Fit in Machine Learning Types?
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ML 101: Where Do Decision Trees & Random Forests Fit in Machine Learning Types?
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About this listen
After learning the main types of machine learning, this short Machine Learning 101 episode answers a practical question: where do Decision Trees and Random Forests fit? We explain why these models are most commonly used for supervised learning—both classification (spam vs not spam, fraud vs not fraud) and regression(house prices, delivery time). We also touch on how tree-based methods can be adapted for unsupervised tasks like anomaly detection, but why their standard form is supervised. Clear real-world examples included.
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