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Running a targetted marketing ads on facebook. The company wants to anaylze customer behaviour by predicting which customer clicks on the advertisement

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Machine Learning - Logistic Regression

Facebook--PredictCustumer-Click

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Background

Running a targetted marketing ads on facebook. The company wants to anaylze customer behaviour by predicting which customer clicks on the advertisement. Customer data is as follows:

Inputs:

  • Name
  • e-mail
  • Country
  • Time on Facebook
  • Estimated Salary (derived from other parameters)

Goals

  • Split the data in Train and Test
  • Train and Test the model in the data set
  • Visualize
  • Predict Click on the ad

How to run

Open Google Colab https://colab.research.google.com/

  • File
  • Upload Notebook
  • Run the Cells

Proccess

Import the data set and visualize the data

  • With Scatter plot

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  • With Box plot

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  • With Histogram

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Transforming the data and Executing a training Test

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With Confusion Matrix, checking on the accuracy

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ploting the boundary using the trained classifier

  • Run the classifier to predict the outcome on all pixels with resolution of 0.01
  • Colouring the pixels with 0 or 1
  • If classified as 0 it will be magenta, and if it is classified as 1 it will be shown in blue

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Ploting all the actual training points

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Visualising the Training set results for Tran and Test

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Running a targetted marketing ads on facebook. The company wants to anaylze customer behaviour by predicting which customer clicks on the advertisement

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