Logistic Regression Simple Explained : The whole magic is under the hood i.e., sigmoid function σ(z)=1/ 1 e−z1 ✨ It is an algorithm and statistical method used in machine learning for binary classification tasks, where the goal is to predict one of two possible outcomes (for example, yes or no) Logistic regression outputs probabilities that a certain event will occur, using the logistic function to transform the linear output of a model into a probability value from 0 to 1. It's used mainly for

Sigmoid activation function clearly explained in python | jupyter notebook