Business Applications Of Predictive Modeling At Scale

KDD '16: The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining San Francisco California USA August, 2016(2016)

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摘要
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 [5]. We will introduce the essential concepts and state of the art in building end-to-end predictive modeling solutions, and discuss the challenges [6], key technologies, and lessons learned from our practice, including case studies of Linkedln feed relevance [1-4] 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.
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关键词
predictive modeling,business analytics,machine learning,machine learning platforms
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