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
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.
Conference venue: Yandex office, Karl-Liebknecht-Straße, 1 (Radisson Blu Hotel), Berlin.



Andreas Braun
Allianz, Head of Global Data and Analytics

Jeff Palmucci
Director of Machine Intelligence

Norbert Wirth
Global Head of Data and Science

Esther Dyson
Yandex, Board Member

Sergey Kravchenko
Boeing, President, Russia and CIS

Arkady Volozh
Yandex, Founder

Norbert Weber
Senior Business
Development Manager

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

Evan Estola
Senior Machine Learning Engineer

Jochen Glaser
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,

Ralf Herbrich
Director of Machine Learning

Reza Khorshidi
Head of Quantitative Analytics

Abraham Greenstein
Manager, machine learning

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