Sketch credit Cynthia Savard

Si PyCon n'était pas assez pour vous, Montréal-Python vous présente sa solution : notre 53e édition! Après une incroyable première journée de sprint, nous rassemblons pour vous quelques uns des meilleurs présentateurs de PyCon, pour encore plus de présentations!

Cette édition spéciale de Montréal-Python est organisé en collaboration avec MTLData, DevOpsMTL et DockerMTL.

Trey Causey: Scalable Machine Learning in Python using GraphLab Create

I'll be giving an overview of how to use GraphLab Create to quickly build scalable predictive models and deploy them to production using just an IPython notebook on a laptop.

Nina Zakharenko: Technical Debt - The code monster in everyone's closet

Technical debt is the code monster hiding in everyone's closet. If you ignore it, it will terrorize you at night. To banish it and re-gain your productivity, you'll need to face it head on.

Olivier Grisel: What's new in scikit-learn 0.16 and what's cooking in the master branch.

Scikit-learn is a Machine Learning library from the Python data ecosystem. Olivier will give an overview and some demos of the (soon to be | recently) released 0.16.0 version.

Jérome Petazzoni: Deep dive into Docker storage drivers

We will present how aufs and btrfs drivers compare from a high-level perspective, explaining their pros and cons. This will help the audience to make more informed decisions when picking the most appropriate driver for their workloads.

Pierre-Yves David: Mercurial, with real Python bites

In this talk, we'll go over on the advantages of Python that helped the project both in its early life when so much feature needs to be implemented, but also nowaday when major companies like Facebook bet on Mercurial for scaling. We'll also point at the drawback of choosing Python and how some work-arounds had to be found. Finally, we'll look at how the choice of Python have an impact on the user too with a demonstration of the extensions system.

Nicolas Kruchten: Lightning talk

Nicolas Kruchten will be giving the first ever public demo of Datacratic's Machine Learning Database (MLDB): a product which is distributed as a Docker image and which uses Python as a plugin and scripting language.

Merci à nos commanditaires spécial pour cet événement: Docker Inc. and LightSpeed Retail


Lundi, le 13 avril 2015

Maison Notman 51 rue Sherbrooke Ouest, Montréal QC H2X 1X2


Réservez votre place gratuitement ici:


  • 6:00pm — Ouverture des portes
  • 6:30pm — Début des présentations
  • 7:30pm — Pause
  • 7:45pm — Suite des présentations
  • 9:00pm — Bière gratuite au Bénélux, à quelques pas de la Maison Notman

Merci à tous nos commanditaires qui rendent cet événement possible

  • Lightspeed Retail
  • Docker Inc.
  • UQÀM
  • Bénélux
  • Outbox
  • Savoir-Faire Linux
  • Caravan
  • iWeb