The dataset includes data from 89973 customer with 10 features
1-Customer income
2-First Buy Data
3-Last Buy Data
4- Average Buy Amount
5- Frequency Level
6- Buy Amount Grade
7- Special Buyer
8- Last Buy Amount
9- Buy Amount Average
10- class
Given a number of elements of customers of a store with certain features, we want to build a machine learning model to identify that
who response to the Advertising Campaign according to the "class" column.
To solve the problem we will have to analyses the data, do any required changed, normalisation, apply a machine learning algorithm, train a model, check the performance of the trained model and iterate with other algorithms until we find the best model.