Data Science, Machine Learning, Marketing, and the Customer Experience

Nate Payne will be giving a talk going over using Data Science, Machine Learning, Statistics and R on real-world data. Here are the details:

With increased access to data, decreasing time, and increased pressure, marketers, business analysts, statisticians, and managers at all levels are constantly faced with the challenge of making sense of complex, correlated, and heteroscedastic data. In order to deal with these challenges at scale and provide answers to stakeholders through their organizations, individuals in these roles - in nearly every discipline - are increasingly looking to machine learning for help. As a Director of Research & Analytics, Nate Payne faces these challenges on a daily basis. To overcome these challenges and provide answers to Nate's clients, Nate and his team, regularly use R to model trends, build visualizations, mine databases, and clean data. In Nate's talk, he intends on illustrating the techniques and tactics from machine learning that can be used to solve useful business and marketing questions. Furthermore, he will show R code, and provide numerous examples from his own experience of the types of problems that various machine / statistical learning algorithms are good at solving, including regression, classification, and clustering algorithms.

BONUS:

We'll also have a few short lightning talks. So far...

• Jamie King from Pulse Energy will speak about their analytics work.

• Jenny Bryan (http://www.stat.ubc.ca/%7Ejenny/) will give a short talk on the UBC Stats grad program, Data Science @ UBC, what's happening at UBC with R.

(If anyone is interested in giving a short 5-to-15 minute long, please let us know.)