Business Applications of Predicitive Modeling at Scale
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Predictive modeling is the art of building statistical models that forecast probabilities and trends of future events. It has broad applications in industry across different domains. Some popular examples include user intention predictions, lead scoring, churn analysis, etc. In this tutorial, we will focus on the best practice of predictive modeling in the big data era and its applications in industry, with motivating examples across a range of business tasks and relevance products. We will start with an overview of how predictive modeling helps power and drive various key business use cases. We will introduce the essential concepts and state of the art in building end-to-end predictive modeling solutions, and discuss the challenges, key technologies, and lessons learned from our practice, including case studies of LinkedIn feed relevance and a platform for email response prediction. Moreover, we will discuss some practical solutions of building predictive modeling platform to scale the modeling efforts for data scientists and analysts, along with an overview of popular tools and platforms used across the industry.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !