Machine Learning and Big Data:
Business Challenges

This special business session of the conference 'Machine Learning: Prospects and Applications' was held on October 8, 2015, in Berlin.
Devoted to the challenges faced by data scientists and business leaders as they implement cutting-edge data science in their day-to-day operations, it explored such questions as:
How can we get machines to learn faster and more accurately?
How can algorithms change the daily life of millions of people?
What ethical and technical questions should a business be aware of before embarking on the big data endeavour?
Businesses continuously try to influence people, both employees and customers.
Why is it controversial to influence some of them in different ways – also known as "an experiment"?
Is it fair to charge different people different prices?
What can you learn from failure?

Session Shedule

 
9-00 – 9-10
Welcome remarks by Jane Zavalishina, CEO Yandex Data Factory.
9-10 – 9-50
RECAP: A report from the scientists from "Machine Learning: Prospects and Applications".
Moderator: Esther Dyson, Yandex board member.
Participants: Arkady Volozh, Yandex, founder; Nathan Intrator, Blavatnik School of Computer Science, Sagol School of Neuroscience and Neurosteer, Professor.
9-50 – 10-20
Case study 1.
Issues and Solutions for Location Classification Using Crowdsourced Data at Scale.
Jeff Palmucci, TripAdvisor, Director of Machine Intelligence.
10-20 – 11-05
Panel 1.
How big data analytics works in the real world.
Moderator: Ivan Yamschikov, Yandex analytics group.
Participants: Reza Khorshidi, AIG, Head of Quantitative Analytics, EMEA; Emanuele De Leonardis, Orange, Global Director, Product Strategy Big Data & Analytics; Jochen Glaser, INTEL, Head of Influencer Sales Group; Ralf Herbrich, Amazon, Director of Machine Learning.
11-05 – 11-30
Coffee break
11-30 – 11-55
Сase study 2.
How mobile data can enable public transport regulation: Motionlogic and Deutsche Telekom case study.
Norbert Weber, Motionlogic, Senior Business Development Manager.
11-55 – 12-40
Panel 2.
How does machine learning foster new business models?
Moderator: Esther Dyson.
Panelists: Sergey Kravchenko, Boeing, President, Russia and CIS; Evan Estola, Senior Machine Learning Engineer, Meetup; Abraham Greenstein, Appnexus, Manager, machine learning.
12-40 – 13-40
Lunch
13-40 – 14-05
Case study 3.
Computer vision. Client's case study.
Alexander Khaytin, Yandex Data Factory, Deputy CEO.
14-05 – 14-50
Is machine learning a game changer in marketing? What are the perspectives and limitations?
Moderator: Norbert Wirth, GfK, Global Head of Data and Science.
Panelists: Andreas Braun, Allianz, Head of Global Data and Analytics; Martin Szugat, Predictive Analytics World Germany, Program Chair.; Raoul Kübler, Ozyegin University, Istanbul
14-50 – 15-00
Closing remarks – Jane and Arkady.
 
Venue
Conference venue: Yandex office, Karl-Liebknecht-Straße, 1 (Radisson Blu Hotel), Berlin.

Speakers

 
 
 

Andreas Braun
Allianz, Head of Global Data and Analytics

Jeff Palmucci
Tripadvisor, 
Director of Machine Intelligence

Norbert Wirth
GfK, 
Global Head of Data and Science
 
 
 

Esther Dyson
Yandex, Board Member

Sergey Kravchenko
Boeing, President, Russia and CIS

Arkady Volozh
Yandex, Founder
 
 
 

Norbert Weber
Motionlogic,
Senior Business
Development Manager

Martin Szugat
Datentreiber, Managing Director;
Predictive Analytics World Germany,
Program Chair

Evan Estola
Meetup,
Senior Machine Learning Engineer
 
 
 
 

Jochen Glaser
INTEL,
Head of Influencer Sales Group
 

Nathan Intrator
Tel Aviv University,
Professor of Computer
Science and Neuroscience

Emanuele De Leonardis
Orange, Global Director,
Product Strategy
Big Data & Analytics
 
 
 

Raoul Kübler
Ozyegin University,
Istanbul
 

Ralf Herbrich
Amazon,
Director of Machine Learning

Reza Khorshidi
AIG,
Head of Quantitative Analytics
 
 
 
 

Abraham Greenstein
Appnexus,
Manager, machine learning

Sponsors and Partners

 
 
For any additional information, please contact us:
ydf-conference@yandex-team.com