Objective:

The objective of the project is to give a hands-on experience of Machine Learning and Artificial Intelligence to the Participant. The participant will learn to apply ML-AI algorithms to predict what kind of viewers are likely to view a new tv show yet to be launched or likely viewership for an extended season.

To understand propensity modeling, it is nothing but a statistical score card given to the customer. Interesting use cases include: Which customers are likely to respond to a particular offer? Which customers are likely to extend their subscriptions? And so on.

Methodology:

Participants will research and gather publicly available customer purchase/sales data from various sources. They will use algorithms related to classification and to predict the likeliness of response. They extend this work and develop custom metrics and score them according to the scores associated with each customer/viewer.

Benefits:

This project will help participants to have first-hand experience of ML in retail industry. Adding to it, it establishes sufficient understanding of use-cases in retail industry. Applications of PM run across industries like media, tele communications, retail and so on.

Duration: 3-6 Months (Online – Offline, Instructor based)