Montreal Data

Articles, nouvelles et annonces

Autodata: Automating common data operations
The community has been automating common procedures including data loading, exploratory data analysis, feature engineering, and model-building. This new world of autodata tools takes some agency away from practitioners in exchange for repeatability and a reduction in repetitive error-prone work. Autodata tools, when used responsibly, can standardize data workflows, improve the quality of models and reports, and save practitioners time.
In this post, I’ll first list some open source projects in the space of autodata, and then take a stab at what the future of autodata could look like. There’s no reason to trust the second part, but it might be fun to read nonetheless.

Awesome production machine learning
This repository contains a curated list of awesome open source libraries that will help you deploy, monitor, version, scale, and secure your production machine learning.

[Faction A] Azure Purview: la gouvernance unifiée des données
Vidéo du webinaire. Ce que vous apprendrez :
- Les enjeux typiques que rencontrent les organisations en termes de gouvernance des données.
- Les éléments essentiels d’une robuste gouvernance des données.
- Les caractéristiques de Microsoft Azure Purview.

McKinsey: Insurance 2030—The impact of AI on the future of insurance
The industry is on the verge of a seismic, tech-driven shift. A focus on four areas can position carriers to embrace this change.

Papers Without Code
The goal of this is to save the time and effort of researchers who try to reproduce the results of a paper that is unreproducible. It could either be due to the paper not having enough details or the method straight up not working. In either case, authors will be given the opportunity to respond. The hope is this saves people time and disincentivizes unreproducible papers.

Événements

Developing Data Democratization in Government
Thursday 08 April 2021 @ 15:00
Join Alex Scriven, a Senior Data Scientist from the New South Wales Government in Sydney, Australia as he breaks down what data democratization means in a government environment. He will also provide specific, actionable best practices for growing data democratization in government and outline some interesting case studies for what can happen when democratization in government begins to take hold.

Meetup PyData Montreal #19
Thursday 22 April 2021 @ 18:00
6:00 pm — Introductions
6:10 pm — "Text Extensions for Pandas" by Frederick Reiss
7:10 pm — "Introducing Elyra: Extending JupyterLab for AI" by Luciano Resende
8:00 pm — Wrap-up

Intelligence artificielle et cybersécurité: protégez vos innovations!
Friday 23 April 2021 @ 12:00
Institut intelligence et données (IID) de l'ULaval: Comment identifier les risques de cybersécurité spécifiques à l’IA? Quelles sont les bonnes questions à se poser en matière de cybersécurité avant de se lancer dans un projet d’IA? Quelles sont les solutions de sécurisation possibles? Comment les choisir et les mettre en œuvre?

Meetup: How to QA your ML models
Wednesday 28 April 2021 @ 16:00
Simon Dagenais from Snitch AI will go through the reasons behind using an efficient validation framework that goes beyond the common metrics used by ML practitioners and why these tests matter when building high-quality models.

École d'été 2021 en journalisme de données
Monday 31 May 2021 @ 09:00
Vous apprendrez à programmer afin de répondre aux questions qu'un(e) chercheuse(eur) en sciences humaines et sociales ou qu'un(e) journaliste peut se poser. Vous allez d'abord automatiser la collecte d’information sur un site web. Ensuite, vous allez créer votre algorithme pour trier et analyser les données récoltées. Et pour finir, vous allez construire une visualisation de données interactive pour le web.

QUAND?
La formation dure cinq jours: du 31 mai au 4 juin 2021, de 9h00 à 17h00.

COMBIEN ÇA COÛTE?
C’est gratuit! (Et ce n'est pas vous le produit)