Project for "Supervised Learning" course
Owners:
- Mauro Venticinque @ Dept of Economics and Business
- Angelo Schillaci @ Dept of Economics and Business
- Daniele Tambone @ Dept of Math and Computer Science
In this project, we analyze data from a Portuguese banking institution’s direct marketing campaigns to identify key factors influencing customer subscription to term deposits. The dataset includes client demographics, previous campaign interactions, and economic indicators. Our goal is to develop insights that will enhance the effectiveness of future marketing strategies. By applying supervised learning techniques, we aim to predict customer responses and optimize outreach efforts for better engagement and conversion rates.
The report will begin with an Exploratory Data Analysis, examining the variables and their relationship with the target attribute (subscribed) to identify the most influential factors.
You can view the final result of this report here.