Montreal Data

Articles, nouvelles et annonces

Federal and Quebec governments launch AI centre in Montreal
The International Centre of Expertise in Montréal for the Advancement of Artificial Intelligence (ICEMAI) will strengthen innovation and the commercialization of AI technology. The centre will work with the government’s Advisory Council on Artificial Intelligence and other organizations.

Google Cloud’s AI Adoption Framework
Our framework for AI adoption provides a guide to technology leaders who want to build an effective AI capability, one that enables them to leverage the power of AI to enhance and streamline their business, smoothly and smartly. The framework is informed by Google’s own evolution, innovation, and leadership in AI, including experience deploying AI in production through products such as Gmail and Google Photos.

The Ultimate Guide to Deploying Machine Learning Models
I decided to write a comprehensive blog series on how to deploy ML models to production. Many of these blog posts include tutorial-style code. But my goal isn’t to code up a complete system. My goal is to educate data scientists, ML engineers, and ML product managers about the pitfalls of model deployment and describe my own model for how you can deploy your machine learning models.

Nitpicking Machine Learning Technical Debt
I recently revisited the paper "Hidden Technical Debt in Machine Learning Systems" (Sculley et al. 2015). [...] This post covers some of the relevant points of the Tech Debt Paper, while also giving additional advice on top that’s not 5 years out of date. Some of this advice is in the form of tools that didn’t exist back then…and then some is in the form of tools/techniques that definitely did exist that the authors missed a huge opportunity by not bringing up.

Beyond Pandas: Spark, Dask, Vaex and other big data technologies battling head to head
API and performance comparison on a billion rows dataset. What should you use?

spacy-streamlit: spaCy building blocks for Streamlit apps
This package contains utilities for visualizing spaCy models and building interactive spaCy-powered apps with Streamlit. It includes various building blocks you can use in your own Streamlit app, like visualizers for syntactic dependencies, named entities, text classification, semantic similarity via word vectors, token attributes, and more.

Événements

Meetup Montréal-Python 78 – Ingenious Rewrite
Monday 29 June 2020 @ 17:30
Carl Meyer, membre de l'équipe d'expertise technique de Django et développeur chez Instagram va nous parler de typage en Python avec une étude de cas sur une large base de code.

The Web-Enabled Simulation (WES) research agenda
Tuesday 30 June 2020 @ 12:00
This talk will cover the Web-Enabled Simulation (WES) research agenda, and describe FACEBOOK’s WW system. WW is used to simulate social media interactions on an infrastructure consisting of hundreds of millions of lines of code. The WES agenda draws on research from many areas of study, including Search Based Software Engineering, Machine Learning, Programming Languages, Multi Agent Systems, Graph Theory, Game AI, and AI Assisted Game Play.

Using Python with a Massively Parallel Database to Predict COVID-19 Numbers
Tuesday 07 July 2020 @ 14:00
Python is a powerful programming language that is a good choice for many types of analytics. It is rapidly becoming the language of choice for scientists and researchers of many types. Now by combining a massively parallel (MPP) database like Vertica with Python, you can overcome many scale and analytics challenges that can limit Python users.

Google Cloud Next OnAir
Tuesday 14 July 2020 @ 09:00
La conférence annuelle de Google Cloud sera en ligne cette année. Celle-ci se tiendra sur 9 semaines avec un thème différent à chaque semaine, incluant: Data Analytics, Cloud AI, Data Management & Databases, et plus encore.