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Predicting if internet users will click on the advertisement or not using a Logistic Regression Model

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Advertising Click Prediction

In this project, we are going to work on some synthetic advertising dataset, indicating whether or not a particular internet user has clicked on an Advertisement.

The goal is to predict if a user would click on an advertisement based on the features of the user.

In the following you can find the description of the features included in the dataset:

  • 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

The sources used to create this tutorial are the following:

  1. Udemy's course Python for Data Science and Machine Learning Bootcamp.
  2. The book An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani.

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Predicting if internet users will click on the advertisement or not using a Logistic Regression Model

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