Using Data Science to make products count

The following tasks were performed during this project:

1. Performed exploratory data analysis on a data set containing 200 columns and 2500 records, to gain insight on demographic distribution, and to identify and handle missing values through data imputation.
2. Used K-modes clustering to identify devices being used by different types of users.
3. Trained Support Vector Machines to gauge optimal advertisement channels to be utilized by the marketing firm to ensure maximum reach.

This repository contains the following:

1. A detailed report
2. Presentation