In this video, we will cover the theory and intuition of Logistic Regression classifier and will include a detailed case study to predict whether customers will click on Facebook ads or not based on their features.
Logistic regression is used to predict binary outputs with 2 possible values (0 or 1).
Logistic model output can be one of two classes: pass/fail, win/lose, healthy/sick.
Linear regression is unbounded, so logistic regression will be better candidate in which the output value ranges from 0 to 1.
I hope you will find the video useful and informative.
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