Boston useR Meetup - with SPLASH Boston 2018

We will have two presentations for this meetup
#1: Massive Scale Data Science in R with Spark on Databricks with Bryan Cafferky
#2: Supervised and Unsupervised Machine Learning Techniques with Bryan Butler

Bio:
Bryan Cafferky:
Bryan Cafferky is a Microsoft Data Science and AI Technical Solutions Professional focused on helping healthcare customers understand and implement Data Analysis, Machine Learning, and AI solutions. He is a Microsoft 2017 Data Platform MVP and a 2016 Cloud and Data Center Management MVP. Bryan is the author of Pro PowerShell for Database Developers by Apress, available on Amazon. He leads The RI Microsoft BI User Group, and The Greater Boston Area Data Science, Machine Learning, and AI Group. He has been working with the SQL Server stack since 1997 and implemented projects in the banking, insurance, e-commerce, utility, and health care industries. He holds a bachelor of science in computer information systems and a Master’s degree in Business

Bryan Butler:
Bryan Butler is a Lead Data Scientist at the Hanover Insurance Group. His work is mainly focused on applying text analytics and natural language processing to predicting claims and underwriting risks. While having additional experience in both banking and marketing research, he spent most of his career in the insurance industry modeling the impacts of natural catastrophes (hurricanes, earthquakes and extra-tropical cyclones) as well as terrorist attacks, and stress testing capital models. His previous experience includes working in reinsurance in Bermuda, and at Lloyd's of London.

Abstracts:

#1: Massive Scale Data Science in R with Spark on Databricks
Spark is the hottest Big Data scale out platform in the world. With the SparklyR and SparkR packages, you can massively scale your data analysis and machine learning scripts. In this presentation, we’ll show you how handling Big Data can be easy and fun and we can use good old R to do it. You like dplyr? Not a problem, so does Spark thanks to the SparklyR package. And we can do it all in the powerful Databricks notebook which also lets us integrate Python, Scala, and SQL into the same program. So get your popcorn and take a seat for the greatest Big Data show on earth!

#2: Supervised and Unsupervised Machine Learning Techniques
Marketing is constantly focused on identifying and targeting segments. There are many ways to create segments based on buying patterns, etc. However, more challenging is understanding the psychographic characteristics of customers. One method of marketing research used to do this is the survey. In this short presentation, we'll look at how to combine both supervised and unsupervised machine learning techniques to marketing surveys and extract behavioral/psychographic segments.

We're also partnering up with the SPLASH conference for the November Meetup. For more information on SPLASH - https://2018.splashcon.org/ and for information on how you can win a free registration to the conference please email rachael@rstudio.com

*FYI for everyone - this happens to be on election day

Location:
MIT Computer Science & Artificial Intelligence Laboratory
Room 2: 32-D463
The Stata Center
32 Vassar Street, Cambridge MA 02139

Directions to Star Conference Room, 32-D463
The Star Conference room is on the 4th floor of the Dreyfoos Wing in the Stata Center (Building 32).

Enter Building 32 at the front entrance and proceed straight ahead; there will be elevators to the right. Take the elevators to the 4th floor; exit to the left and then turn right at the end of the elevator bank. At the end of the short corridor, turn right, just before the R&D Dining room. The Star Conference Room is straight ahead, just past a set of stairs.