Path to AI

What is to be Done When Everything Can be Faked | Shaun McGirr, Cox Automotive UK

From Silos to Self-Service: Data Transformation at GE Aviation | Jon Tudor, GE Aviation

Are You Vulnerable to Adversarial Machine Learning? | Celeste Fralick, McAfee

Cyber Risk Analytics: The Next Frontier | Paul Guthrie, Envelop

From Us, To Us: An Inclusivity Architecture | Brandeis Marshall, Spelman College

Becoming an Intelligent Organization in the Age of AI | Jeff McMillan, Morgan Stanley

What’s At Stake With Your Data Projects Operationalization? | Romain Fouache, Dataiku

Democratizing Automated Forecasting | Lukas Stroemsdoerfer, Mercedes-Benz

Online Conversion Modeling Combining CRM-Data and Online Behavior | DPG Media

Generative Adversarial Networks for Finance | Alexandre Hubert, Dataiku

EGG AMS 2019 Opening Plenary | Hylke Visser, Dataiku

Ethical Enterprise AI – A Guideline or Compass? | Martin Leijen, Rabobank

Synthetic Data: How Do We Manage Them? | Armando Vieira, Hazy

Cleaner Oceans Through AI and Data Science | Bruno Sainte-Rose, The Ocean Cleanup

Fueling Digital Transformation Within the Enterprise | Ayan Bhattacharya, Deloitte

AI in Retail: Building a Brilliant Shoe Discovery System | Antonis Argyros, SafeSize

Diversity and Inclusion in Data Science | Noelle Silver, HackerU

The Law of Averages to Deal with Data Science Frustration | Adrian Badi, Demant

The Growing Pains, Pitfalls & Future for a Data Science Team in a Hyper-Growth Company | Shaun Moate, DAZN

AI Adoption in the Enterprise | Jacob Wilson, PwC

AI + Human Intuition = Differentiated Insights | Jeff McMillan, Morgan Stanley

Augmented Human Intelligence | Walid Mehanna, Daimler

The Spirit of the City: Capturing Network-Generated Data for Better Cities | Luca Maria Aiello, Nokia Bell Labs

How to Make a Success of Data Science | Jan Teichmann, Zoopla

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