Unlocking the Mystery of Logistic Regression: A Simple Explanation 🤖

Ever wondered how machines decide yes or no?

Unlike Linear Regression, which predicts continuous outcomes, Logistic Regression focuses on binary classification - predicting one of two outcomes such as true/false or spam/not spam.

It uses the logistic (sigmoid) function to convert linear outputs into probabilities between 0 and 1, giving insight into how likely an event is to happen.

Here’s the beauty: the model keeps refining its weights to reduce errors and boost accuracy.

Simple, interpretable, and incredibly effective Logistic Regression remains one of the best starting points to understand how classification models think.

C: 3 Minute Data Science

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