All scikit-learn consortium partners
are pleased to invite you
to the first annual workshop

Tuesday, May 28, 2019 from 10:00am to 7:00pm

Welcome coffee from 9:30am –

BNP Paribas Cardif – 8 rue du Port, Nanterre
Access

Sorry, registrations are now closed.

 

 

 

 

Schedule

[ All presentations in English ]

Welcome address by Stanislas Chevalet, Deputy Chief Executive Officer, Transformation & Development, BNP Paribas Cardif

10.05am: Gaël Varoquaux / Inria
Foreword: the scikit-learn consortium
[See the presentation]

10.20: Roman Yurchak / Inria – Symerio
Tutorial: scikit-learn new features. Preprocessing and imputation methods, estimators for clustering, supervised learning
[Slides from the tutorial and the tutorial notebook]

11.40: Xavier Dupré / Microsoft
ONNX: machine learning model persistence
[See the presentation]

12.00: Jérémie du Boisberranger / Inria
Tutorial: questions of performance in scikit-learn. Parallelism, memory, low-level optimizations
[See the tutorial notebook]

1.00pm: Lunch

2.00: Xavier Renard / AXA
Whitening ML black boxes: where do we stand?
[See the presentation]

2.20: Guillaume Lemaître / Inria
Tutorial: scikit-learn interpretability, linear and tree-based models
[See the tutorial notebook1 and notebook2]

3.40: Peter Entschev / Nvidia
Nvidia Distributed GPU Machine Learning with RAPIDS and Dask
[See the presentation]

4.00: Tung Lam Dang / BNP Paribas Cardif
Scikit-learn: a tool for better model risk governance @ BNPP Cardif
[See the presentation]

4.20: Laurent Duhem / Intel
Speeding up scikit-learn on Intel architectures
[See the presentation]

4.40: Léo Dreyfus-Schmidt & Samuel Ronsin / Dataiku
LeaveNoOneOut: Building a ML platform for everyone
[See the presentation]

5.00: Anton Bossenbroek / BCG
Rapid and collaborative fair data science deployment in strategy consulting

5.20: Olivier Grisel / Inria
Wrap up and perspectives
[See the presentation]

5.30: Round-table discussion: Open source, a model for AI and data science?

6.00: Closing cocktail