Practical Data Science with R

We are excited to be having John Mount and Nina Zumel, authors of Practical Data Science in R (http://www.manning.com/zumel/), stopping by to speak about the data science process described in their book. Hope to see many of you there!

Schedule

6:30 - 7:00pm Social (food + beer served)
7:00 - 8:00pm Talk
8:00 - 8:30pm Social

Talk

Data Science is the current popular term for the entire process of using data to build predictive models. The process includes: requirements gathering, data architecture, design of experiments, statistics, machine learning, software engineering, and presentations. John Mount will talk about the processes of data science and his new book: Practical Data Science with R (Manning Publications Co, 2014). This book is designed to teach how to solve business analytics problems using repeatable techniques with the R statistical workbench. From this talk you should get a basic familiarity with ideas used to:

• Effectively scope and organize data science projects* Be an effective consumer of machine learning results* Choose among important model performance criteria* Produce effective data visualizations
  This talk should be of interest to both those who work with data scientists and to practicing data scientists.

Bio

John Mount started his advanced education in mathematics as U.C. Berkeley and holds a Ph.D. in computer science from Carnegie Mellon. He has worked as a computational scientist in biotechnology, as a stock trading algorithm designer, and has managed a research team for Shopping.com (now eBay). He is a principal consultant at Win-Vector LLC a San Francisco data science consultancy. John is an author of Practical Data Science with R, Manning Publications, 2014), blogs about technical issues at http://www.win-vector.com/blog/ , and is active in the San Francisco Rotary.

Nina Zumel started her advanced education in electrical engineering at U.C Berkeley and holds a Ph.D. in robotics from Carnegie Mellon. She has worked as a scientist at SRI International, as chief scientist of a price optimization company and founded a contract research company. Nina is a principal consultant at Win-Vector LLC a San Francisco data science consultancy. Nina is the first author of Practical Data Science with R, Manning Publications, 2014), blogs about technical issues at http://www.win-v http://ector.com/blog/ , and writes about myths at http://multoghost.wordpress.com (http://multoghost.wordpress.com/).