ML 101: Regression Made Simple — Linear, Logistic, Multivariate & Polynomial
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ML 101: Regression Made Simple — Linear, Logistic, Multivariate & Polynomial
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About this listen
In this Machine Learning 101 episode, we explore regression—one of the simplest and most practical ML techniques—using clear, non-technical examples. We cover Linear Regression (predicting numbers like house prices), Logistic Regression (yes/no decisions using probability, like spam or fraud), Multivariate/Multiple Regression (using many factors at once), and Polynomial Regression (capturing curved relationships like diminishing returns). You’ll also learn how to choose the right approach, how to evaluate results, and a quick note on bias and responsible use.
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