Difference between linear and logistic regression

Question

Accepted Answer

Linear regression is used for continuous variables, while logistic regression is used for binary classification.

Linear regression predicts continuous values, while logistic regression predicts probabilities between 0 and 1.
Linear regression uses a linear equation to model the relationship between the independent and dependent variables.
Logistic regression uses the logistic function to model the probability of a binary outcome.
Linear regression is suitable for predicting house prices, while logistic regression is suitable for predicting whether a customer will buy a product.
Linear regression minimizes the sum of squared errors, while logistic regression minimizes the log loss.

Popular interview questions of Ai Ml Engineer