Innovation for Sustainable Growth | Carlo Purassanta, Microsoft Innovation for Sustainable Growth | Carlo Purassanta, Microsoft
What’s At Stake With Your Data Projects Operationalization? | Romain Fouache, Dataiku What’s At Stake With Your Data Projects Operationalization? | Romain Fouache, Dataiku
MLops: from buzzword to reality | Arnaud Canu, Eulidia MLops: from buzzword to reality | Arnaud Canu, Eulidia
How to reposition a data mining team in a data center of excellence | Arnaud Foujols, Monoprix How to reposition a data mining team in a data center of excellence | Arnaud Foujols, Monoprix
How to push a customer scoring system to production with a reduced data science team | Hayet Bezzeghoud & Adrien Basso-Blandin, Finexkap How to push a customer scoring system to production with a reduced data science team | Hayet Bezzeghoud & Adrien Basso-Blandin, Finexkap
From Us, To Us: An Inclusivity Architecture | Brandeis Marshall, Spelman College From Us, To Us: An Inclusivity Architecture | Brandeis Marshall, Spelman College
Cyber Risk Analytics: The Next Frontier | Paul Guthrie, Envelop Cyber Risk Analytics: The Next Frontier | Paul Guthrie, Envelop
KI 2.0: KI bei Non-Tech Unternehmen | Alexander Thamm, Alexander Thamm GmbH KI 2.0: KI bei Non-Tech Unternehmen | Alexander Thamm, Alexander Thamm GmbH
The pillars of an innovative data strategy | Nicolas & Steve, CMA CGM The pillars of an innovative data strategy | Nicolas & Steve, CMA CGM
Which organizational strategies are required to innovate in production? | Sébastien Berard, Euronext Which organizational strategies are required to innovate in production? | Sébastien Berard, Euronext
Understanding Consumer Behavior | ft. Unilever & Capgemini Understanding Consumer Behavior | ft. Unilever & Capgemini
Cleaner Oceans Through AI and Data Science | Bruno Sainte-Rose, The Ocean Cleanup Cleaner Oceans Through AI and Data Science | Bruno Sainte-Rose, The Ocean Cleanup
Convenient and Flexible ML Pipelines with Kubeflow | Mattias Arro, Subspace AI Convenient and Flexible ML Pipelines with Kubeflow | Mattias Arro, Subspace AI
What is to be Done When Everything Can be Faked | Shaun McGirr, Cox Automotive UK What is to be Done When Everything Can be Faked | Shaun McGirr, Cox Automotive UK
Conversational AI and NLP Use Cases at Uber | Franziska Bell, Uber Conversational AI and NLP Use Cases at Uber | Franziska Bell, Uber
Can We Make AI Likeable? | Florian Douetteau, Dataiku Can We Make AI Likeable? | Florian Douetteau, Dataiku
Getting from 1 to 100 Users With Dataiku | Roberto Amador, Johnson & Johnson Getting from 1 to 100 Users With Dataiku | Roberto Amador, Johnson & Johnson
The Law of Averages to Deal with Data Science Frustration | Adrian Badi, Demant The Law of Averages to Deal with Data Science Frustration | Adrian Badi, Demant
Navigating the Gender Pay Gap | Ben Montgomery, Dataiku Navigating the Gender Pay Gap | Ben Montgomery, Dataiku
Users Floating in Space: A Study in Recommendations | Tyler Neylon, Unbox Research Users Floating in Space: A Study in Recommendations | Tyler Neylon, Unbox Research
The Growing Pains, Pitfalls & Future for a Data Science Team in a Hyper-Growth Company | Shaun Moate, DAZN The Growing Pains, Pitfalls & Future for a Data Science Team in a Hyper-Growth Company | Shaun Moate, DAZN
Challenges et enjeux lors de l’opérationnalisation de projets data | Showroomprivé, Dataiku Challenges et enjeux lors de l’opérationnalisation de projets data | Showroomprivé, Dataiku
Livestream with Greg Nelson | Beyond Unicorns: Designing the Workforce of the Future Livestream with Greg Nelson | Beyond Unicorns: Designing the Workforce of the Future
Panel: Magical Experiences and Greater Well-Being | Panel with Disney, Warner Media, Blue Cross Blue Shield Panel: Magical Experiences and Greater Well-Being | Panel with Disney, Warner Media, Blue Cross Blue Shield