The Data Science Food Chain | Shaun McGirr, Dataiku The Data Science Food Chain | Shaun McGirr, Dataiku
The pillars of an innovative data strategy | Nicolas & Steve, CMA CGM The pillars of an innovative data strategy | Nicolas & Steve, CMA CGM
AI in Retail: Building a Brilliant Shoe Discovery System | Antonis Argyros, SafeSize AI in Retail: Building a Brilliant Shoe Discovery System | Antonis Argyros, SafeSize
Can We Make AI Likeable? [in French] | Florian Douetteau, Dataiku Can We Make AI Likeable? [in French] | Florian Douetteau, Dataiku
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
Collaborative Data Science at DAZN | Luke Clark & Andrea Salvati, DAZN Collaborative Data Science at DAZN | Luke Clark & Andrea Salvati, DAZN
MLops: from buzzword to reality | Arnaud Canu, Eulidia MLops: from buzzword to reality | Arnaud Canu, Eulidia
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
Data, a factor of CRM transformation | Remi Mathieu & Alexis Miginiac, SNCF Data, a factor of CRM transformation | Remi Mathieu & Alexis Miginiac, SNCF
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
Demokratisierung von Data Science bei Mercedes Benz Finance | Statworx, Mercedes Benz Demokratisierung von Data Science bei Mercedes Benz Finance | Statworx, Mercedes Benz
Synthetic Data: How Do We Manage Them? | Armando Vieira, Hazy Synthetic Data: How Do We Manage Them? | Armando Vieira, Hazy
Generative Adversarial Networks for Finance | Alexandre Hubert, Dataiku Generative Adversarial Networks for Finance | Alexandre Hubert, Dataiku
