How to Make Our World Better Through Machine Learning

Happy New Year folks!

We are proud and excited to announce our first ever Meetup happening on January 30, 2020, 5:00 to 7.30pm at MILA (6650 St Urbain); sponsored by QuantumBlack, a McKinsey company.

There will be couple of inspiring talks by amazing people, lots of networking along with pizza and drinks.

Please RSVP!

Agenda:
5:00pm - 5:30pm: Welcome / Networking / Introductions
5:30pm - 6:00pm : "Quotient Social or how to make our world better through Machine Learning " talk by Hervé Mensah, Founder of Quotient Social
6:00pm - 6:30pm: "Putting more advanced predictive models to work" talk by Amir Danak, Principal Data Scientist at QuantumBlack
6:30pm - 7:30pm: Networking / Closing

Title:
Quotient Social or how to make our world better through Machine Learning

Speaker:
Hervé Mensah

Abstract:
Founded in September 2017 by Éric Nguyen and Hervé Mensah, Quotient Social is a non-profit organization aiming at offering a range of advanced analytics services to many philanthropic societies, such as as social foundations, enterprises, firms or NGOs.

Hervé Mensah will relate in details the story behind the journey of this NGO that makes rhyme Social and Data Science, the business model that supports it, how the projects started and the several issues it encountered in the world of philanthropy

Title:
Putting more advanced predictive models to work

Speaker:
Amir Danak

Abstract:
What does it take to apply machine learning and deep learning solutions in practice?

More and more businesses, from a growing range of industries, are weaving in machine learning and - particularly deep learning into their products and core processes. This is reshaping software development, and in turn career paths of data scientists and data engineers across different industries.

In this talk, we will discuss how advanced predictive models are changing software engineering, using not only code but also data as the foundation of modern digital solutions. What this means to the roles and responsibilities of data professionals and deep learning practitioners. Why it is imperative to follow software engineering principles in developing analytical products and services. And, what are some of the new protocols and frameworks to enable development of impactful deep learning solutions.