Too Long; Didn't Read
Logistic regression is the most famous <a href="https://hackernoon.com/tagged/machine-learning" target="_blank">machine learning</a> <a href="https://hackernoon.com/tagged/algorithm" target="_blank">algorithm</a> after linear regression. In a lot of ways, linear regression and logistic regression are similar. But, the biggest difference lies in what they are used for. Linear regression algorithms are used to predict/forecast values but logistic regression is used for classification tasks. If you are shaky on the concepts of linear regression, <a href="https://towardsdatascience.com/introduction-to-machine-learning-algorithms-linear-regression-14c4e325882a" target="_blank">check this out</a>. There are many classification tasks done routinely by people. For example, classifying whether an email is a spam or not, classifying whether a tumour is malignant or benign, classifying whether a website is fraudulent or not, etc. These are typical examples where machine learning algorithms can make our lives a lot easier. A really simple, rudimental and useful algorithm for classification is the logistic regression algorithm. Now, let’s take a deeper look into logistic regression.