Transform probability to linear form like Linear Regression using Odds ratio
Unlike linear regression, it handles non-linear relationships well while still being mathematically treatable as linear.
It uses a sigmoid function to output values between 0 and 1, maximizing the log-likelihood.

to make convex cost function

Logistic Regression Notion
This leads to described by Bernoulli Distribution
the Likelihood function is
you can use Newton–Raphson method or Stochastic Gradient Descent and prior one achieves faster convergence or IRLS is much faster
difference between Linear Regression is that usage of sigmoid function or logistic function
a change of one unit of feature changes the odds ratio by a factor