Track: Applied Data Science and Machine Learning


Day of week:

Now that we're flush with opportunities to collect data, just how much can we do with it today? How much can we learn, how quickly can we prescribe action and what are the most valuable questions to ask of our data? This track explores all of the above with the latest production ready techniques and technologies within data science and machine learning. We bring you the leaders in the data science from data driven companies that have honed techniques that you can walk away with and use today. The explosion of data processing, learning, understanding and visualization tools has made this a more accessible field than ever and our lineup will share the latest ready for use in production.

10:40am - 11:30am

by Chris Sanden
Senior Analytics Engineer @ Netflix

At Netflix we strive to provide an amazing experience to each member, winning the "moments of truth" where they decide what entertainment to enjoy. To accomplish this we need to maintain high availability across our systems. However, humans cannot continuously monitor the status of all these systems making it critical for us to have tools that analyze our system environments and make intelligent operational decisions in real-time.

This talk will discuss how Netflix uses data mining...

11:55am - 12:45pm

by Vaclav Petricek
Director, Data Sciences at Live Nation Entertainment

Ticketmaster, the biggest primary ticket issuer and Live Nation, the biggest concert promoter in the world make it possible for hundreds of millions of fans to have a blast at tens of thousands of shows on sale at any point in time.

When U2 or Lady Gaga tickets go on sale the burst of traffic is insane. Even during such crazy times Machine Learning has to:

i) Provide fans with Real-time event recommendations
ii) Detect Bots and ticket scalpers before they snatch tickets...

1:45pm - 2:35pm

by Sandy Ryza
Data Scientist at Cloudera

Under reasonable circumstances, how much can you expect to lose? The financial statistic Value at Risk (VaR) seeks to answer this question. Since its development on Wall Street soon after the stock market crash of 1987, VaR has been widely adopted across the financial services industry.

Some organizations report the statistic to satisfy regulations, some use it to better understand the risk characteristics of large portfolios, and others compute it before executing trades to help make...

3:00pm - 3:50pm

by Rowan Vasquez
Researcher at Twitter

As social networking ad products have become prominent, the need to prove their efficacy has risen in importance. We utilize a data science methodology to determine the offline impact of an online sales travel campaign. We explain how to use Pig and R to process geo-location information in Hadoop and determine whether a user was motivated to pursue action offline after online campaign exposure, ultimately finding a statistically significant impact.

5:00pm - 7:00pm

Open Space

Join Rob Witoff, our speakers, and other attendees for Applied Data Science and Machine Learning Open Space. Stay for questions and share war stories!

What is Open Space?

Open Space is a kind of unconference, a simple way to run productive meetings for 5 to 2000 or more people, and a powerful way to lead any kind of organization in everyday practice and extraordinary change.


4:20pm - 4:25pm

by Rob Witoff
Head of Data Science at Coinbase (form. NASA)

Mini talks intro
4:25pm - 4:35pm

by David Beyer
‎Investor at Amplify Partners

The Machine Intelligence Landscape: A Venture Capital Perspective
4:35pm - 4:45pm

by Olaf Carlson-Wee
Head of Risk at Coinbase

The future of global, trustless transactions on the largest graph: blockchain
4:45pm - 4:55pm

by Richard Minerich
Director of Research and Development at Bayard Rock

Algorithms for Anti-Money Laundering
Host: Rob Witoff Head of Data Science at Coinbase (form. NASA)


Wednesday Jun 10

Thursday Jun 11

Friday Jun 12