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Advertising-data-logistic-regression-project

Advertising Data Analysis

An analysis of advertising data to predict whether a user will click on an ad based on various features.

Table of Contents

  1. Introduction
  2. Dataset
  3. Features
  4. Usage
  5. Results

Introduction

This project performs analysis and prediction on advertising data, aiming to predict whether a user will click on an ad using machine learning techniques.

Dataset

The dataset used for this analysis is included in the project (advertising.csv). It contains various features such as age, daily time spent on the site, and more.

Features

  • Daily Time Spent on Site: Time spent by the user on the site.
  • Age: Age of the user.
  • Area Income: Average income of geographical area.
  • Daily Internet Usage: Daily usage of the internet by the user.
  • Male: Gender of the user.

Usage

Run the Jupyter notebook (advertising_data_analysis.ipynb) to go through the data analysis and machine learning model building process.

jupyter notebook advertising_data_analysis.ipynb

Results

Explore the results of the analysis, including visualizations and the performance of the machine learning model, in the notebook.