From using GPUs to process datasets faster to scaling up workloads dependent on single-node calculation engines in perfectly parallel mode with Spark, and from distributed in-memory filesystems for managing hot data to distributed processing of geospatial and time-series data, we typically cover the cases that need some custom designs and for which there are no out-of-the-box solutions on or off the cloud. Join us to learn and share with us what you know to get things done, faster and better. Technologies that we consider are typically open-source, with permissive licenses.
Meetup group members with names and introduction section properly filled out in their profiles will have priority in attending the meetups in case of limited capacity. Apart from attending the meetups, please do not hesitate to reach out to the organizer if you wish to present your work: an industrial project, an academic paper, or even an interesting work you've done as a hobby in the area of data processing/engineering. Anything technically interesting for our community can be scheduled in an upcoming meetup (a presentation between 5 and 60 minutes).
Each meetup comes with its own terms and conditions specified in its page, but there are also common terms that apply to all. By attending a meetup, you indicate that you have read, understood and accepted these terms: https://www.montrealml.dev/terms . The EDPP Montreal meetup group is the sister group to the ML meetup group, focused on data processing/engineering, and is being organized under the same terms.