In this article we’ll take a deep dive into the Logistic Regression model to learn how it differs from other regression models such as Linear- or Multiple Linear Regression, how to think about it from an intuitive perspective and how we can translate our learnings into code while implementing it from scratch.
Sometimes it’s necessary to split existing data into several classes in order to predict new, unseen data. This problem is called classification and one of the algorithms which can be used to learn those classes from data is called Logistic Regression.
Link: Logistic Regression from scratch
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Photo by Carlos Muza
