Hello everyone and welcome to the logistic regression project exercise overview lecture in this lecture
we're going to be going over the notebook for the logistic regression portfolio project.
Let me go ahead and show you where you can find it.
I wanted to jump to the notebooks now.
All right.
Here I am under the logistic regression folder which is under the machine learning sections folder.
You'll find a notebook labeled logistic regression project and another one labeled logistic regression
project solutions which contains the solutions to the portfolio project.
We'll also be using this advertising that c a c file as the data source for our project.
Let me go ahead and give you a quick walk through logistic regression project.
In this project we're going to be working on some advertising data indicating whether or not a particular
internet user clicked on an advertisement.
We will try to create a model that will predict whether or not they will click on an ad based off of
the features of that user.
And the data set contains several columns and features such as the age of the customer the income of
the customer the topic line of the advertisement where they're from whether or not the consumer was
male what country they're from etc. what you're going to go ahead and do just go through the data import
the libraries you need and do some exploratory data analysis with some visualizations and towards the
end what you'll end up doing is actually the logistic regression part will do a train test split train
the model and check out a classification report.
OK thanks everyone.
Hope you enjoy the project and I'll see you at the next lecture.
We'll go over the solutions.