In this project we will be working with a fake advertising data set, 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 the features of that user.
This data set contains the following features: 'Daily Time Spent on Site': consumer time on site in minutes 'Age': cutomer age in years 'Area Income': Avg. Income of geographical area of consumer 'Daily Internet Usage': Avg. minutes a day consumer is on the internet 'Ad Topic Line': Headline of the advertisement 'City': City of consumer 'Male': Whether or not consumer was male 'Country': Country of consumer 'Timestamp': Time at which consumer clicked on Ad or closed window 'Clicked on Ad': 0 or 1 indicated clicking on Ad
If problem in opening the ipynb file above go to this link: https://nbviewer.jupyter.org/github/samirghouri/Logistic-Regression/blob/master/Logistice%20Regression.ipynb