Machine Learning Linear Regression and Logistic Regression: how to get Log-Odds?

Hello, everyone.

I’ve been on data science path and get to logistic regression on machine learning.

I cant understand how to calculate the log odds for logistic regression. This is the specific lesson.

So, i understand the math behind the log-odds, the log from odds number formula, but how did i get to this number from the linear regression formula? From the lesson, it seems to me that i’m making the same calculations from linear regression, with the same numbers and somehow getting to a different number.

All this stuff of dot product and matrix product, that happens already on linear regression doesnt it? its just the sum of coefficient * value, but seems as if its being presented as justification to reaching log-odds.

Am i missing something here? Feels like i am but i cant figure out what

Thanks for your time!

Ok, so i kept going on the lessons and actually the numbers are not the same?

We wont use the same coefficients and the same intercept, so thats why we will get log-odds from the formula?

But how can a linear function describe the values for sigmoid function?