Presented By O'Reilly and Cloudera
Make Data Work
22–23 May 2017: Training
23–25 May 2017: Tutorials & Conference
London, UK

Schedule: Business case studies sessions

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12:0512:45 Wednesday, 24 May 2017
Location: Capital Suite 15/16
Level: Non-technical
Kim Nilsson (Pivigo)
Average rating: ****.
(4.50, 8 ratings)
More organizations are becoming aware of the value of data and want to get started and scaled up as quickly as possible. But how? Is it possible to get something useful done in five weeks? Kim Nilsson shares her experiences, both good and bad, delivering over 80 five-week data science projects to over 50 organizations, as well as some concrete tips on how to become a data star organization. Read more.
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14:0514:45 Wednesday, 24 May 2017
Location: Hall S21/23 (A)
Secondary topics:  AI, Cloud, Deep learning
Level: Beginner
Kaz Sato (Google)
Average rating: ****.
(4.20, 5 ratings)
TensorFlow is democratizing the world of machine intelligence. With TensorFlow (and Google's Cloud Machine Learning platform), anyone can leverage deep learning technology cheaply and without much expertise. Kazunori Sato explores how a cucumber farmer, a car auction service, and a global insurance company adopted TensorFlow and Cloud ML to solve their real-world problems. Read more.
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14:5515:35 Wednesday, 24 May 2017
Location: Capital Suite 7
Secondary topics:  AI, Deep learning, Logistics
Level: Intermediate
Josef Viehhauser (BMW Group), Dominik Schniertshauer (BMW Group)
Average rating: ****.
(4.60, 5 ratings)
Data-driven solutions based on machine and deep learning are gaining momentum in the automotive industry beyond autonomous driving. Josef Viehhauser and Dominik Schniertshauer explore use cases from the BMW Group where novel machine-learning pipelines (such as those based on XGBoost and convolutional neural nets, for example) support a broad variety of business stakeholders. Read more.