In the previous section, we learned how to predict continuous quantities (for example, the impact of TV advertising on company sales) as linear functions of input values (for example, TV, Radio, and newspaper advertisements). But for other tasks, the output will not be continuous quantities. For example, predicting whether someone is diseased or not is a classification problem and we need a different learning algorithm to perform this. In this section, we are going to dig deeper into the mathematical analysis of logistic regression, which is a learning algorithm for classification tasks.

In linear regression, we tried to predict the value of the output variable *y ^{(i)}* for the

*i*sample

^{th}*x*in that dataset ...

^{(i)}