Logistic Regression

Logistic regression is a widely used statistical and machine learning algorithm primarily used for binary classification tasks. Unlike linear regression, which is designed for predicting continuous numerical values, logistic regression is specifically tailored to handle categorical outcomes with two possible classes (e.g., Yes/No, True/False, 0/1). The purpose of logistic regression is to make predictions and understand the relationship between the independent variables (features) and the dependent variable (binary outcome). Logistic regression is widely used in various fields, including medicine (disease diagnosis), marketing (customer segmentation), finance (credit risk analysis), and natural language processing (sentiment analysis), among others. <a href="https://medium.com/@sharadsisodiya9193/logistic-regression-ade437326da9">Read More</a>