What’s At Stake With Your Data Projects Operationalization? | Romain Fouache, Dataiku What’s At Stake With Your Data Projects Operationalization? | Romain Fouache, Dataiku
Pitfalls of Using ML for Fighting Online Abuse | David Freeman, Facebook Pitfalls of Using ML for Fighting Online Abuse | David Freeman, Facebook
Fueling Digital Transformation Within the Enterprise | Ayan Bhattacharya, Deloitte Fueling Digital Transformation Within the Enterprise | Ayan Bhattacharya, Deloitte
The AI Experts You Need Are Right Beneath Your Nose | Rachel Thomas, Fast.AI The AI Experts You Need Are Right Beneath Your Nose | Rachel Thomas, Fast.AI
Which organizational strategies are required to innovate in production? | Sébastien Berard, Euronext Which organizational strategies are required to innovate in production? | Sébastien Berard, Euronext
Quelle place occupe la data au sein du Groupe La Poste | Pierre-Etienne Bardi, Groupe La Poste Quelle place occupe la data au sein du Groupe La Poste | Pierre-Etienne Bardi, Groupe La Poste
GDPR & the ICO’s AI Auditing Framework | Ali Shah, ICO GDPR & the ICO’s AI Auditing Framework | Ali Shah, ICO
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
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
A Glance at ADA: Aviva’s Algorithmic Decision Agent | Damian Rumble, Aviva A Glance at ADA: Aviva’s Algorithmic Decision Agent | Damian Rumble, Aviva
Navigating the Gender Pay Gap | Ben Montgomery, Dataiku Navigating the Gender Pay Gap | Ben Montgomery, Dataiku
AI in the B2B customer journey | José Ramón Sánchez Martos, Telefónica AI in the B2B customer journey | José Ramón Sánchez Martos, Telefónica
Can We Make AI Likeable? [in French] | Florian Douetteau, Dataiku Can We Make AI Likeable? [in French] | Florian Douetteau, Dataiku
The data science challenges in the European SESAME project | Igor Girard-Carrabin & William Lacheny, ArianeGroup The data science challenges in the European SESAME project | Igor Girard-Carrabin & William Lacheny, ArianeGroup
Can We Make AI Likeable? | Florian Douetteau, Dataiku Can We Make AI Likeable? | Florian Douetteau, Dataiku
Ethical Enterprise AI – A Guideline or Compass? | Martin Leijen, Rabobank Ethical Enterprise AI – A Guideline or Compass? | Martin Leijen, Rabobank
Ethical AI: Inclusivity as a Messy, but Promising Answer | Larry Orimoloye, Dataiku Ethical AI: Inclusivity as a Messy, but Promising Answer | Larry Orimoloye, Dataiku
How to Improve and Innovate Tax Collection by Municipalities | Jan Geert Bakker, Gemeente Amsterdam How to Improve and Innovate Tax Collection by Municipalities | Jan Geert Bakker, Gemeente Amsterdam
Challenges et enjeux lors de l’opérationnalisation de projets data | Showroomprivé, Dataiku Challenges et enjeux lors de l’opérationnalisation de projets data | Showroomprivé, Dataiku
Online Conversion Modeling Combining CRM-Data and Online Behavior | DPG Media Online Conversion Modeling Combining CRM-Data and Online Behavior | DPG Media
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
Transformation data chez Engie GEM | Haga Rabekoto, ENGIE Transformation data chez Engie GEM | Haga Rabekoto, ENGIE
Becoming an Intelligent Organization in the Age of AI | Jeff McMillan, Morgan Stanley Becoming an Intelligent Organization in the Age of AI | Jeff McMillan, Morgan Stanley
Developing ML-Driven Customer Facing Products at Square | Marsal Gavalda, Square Developing ML-Driven Customer Facing Products at Square | Marsal Gavalda, Square
