Pizza & drinks provided
Parking is on the street and you enter our building on the Nueces st. side.
Let's get pumped for the Data Science Pop Up ... a couple of days earlier with a Pre Data Pop Up
6pm- Meet and Greet and be Merry!
6:15pm - Light dinner and drinks served
6:30pm - Ken Sanford (https://www.linkedin.com/in/kenneth-sanford-36818717?authType=NAME_SEARCH&authToken=DPgn&locale=en_US&srchid=2517042741458668264685&srchindex=1&srchtotal=59&trk=vsrp_people_res_name&trkInfo=VSRPsearchId%3A2517042741458668264685%2CVSRPtargetId%3A57161024%2CVSRPcmpt%3Aprimary%2CVSRPnm%3Atrue%2CauthType%3ANAME_SEARCH) - How Can Data Scientists Craft Stellar Pitches
Come learn tips and tricks Ken has learned in his several years of presenting complicated analytical results to audiences, both technical and lay. At the root of successful “selling” of an idea is an understanding of the objective functions of the audience. That is, why do they care about what you have to say? What is the opportunity cost of inaction? Convincing management of the value of advanced analytics on streaming data will become even more important in the growing field of IOT and online learning. In IOT and online learning, it will be especially useful to emphasize the aggregate impact of an improvement to modeling lift and make your case accordingly.
Ken is an Analytics Architect and Evangelist at H2O. Ken is a reformed academic economist who likes to empower customers to solve problems with data. Ken’s primary passion is teaching and explaining. He likes to simplify and tell stories.
7pm -Elias Ponvert (https://www.linkedin.com/in/eponvert) -LeVar (https://github.com/peoplepattern/LeVar)
Machine learning has enormous potential to enable and accelerate insights into data. However, predictive systems using machine learning may be harmful if not rigorously and consistently evaluated for quality and correctness. Unfortunately, there are few resources to encourage rigorous evaluation, especially ones which are not tied to a particular ML framework or methodology.
In Elias' talk he motivates rigorous, regular evaluation of machine learning systems, and discusses why it can be a pain for working data scientists to use it. He presents LeVar, a new open source machine learning evaluation database, which helps overcome these challenges and pains.
Elias is director of data science and People Pattern Corporation. He was a PhD in computational linguistics from the University of Texas in 2011, and a proud Austinite since 2000.
7:30pm - Mingle and Network and get pumped for Data Science Pop Up!