Conference

What I Learned From Tecton's apply() 2022 Conference

What I Learned From Tecton's apply() 2022 Conference

Back in May, I attended apply(), Tecton’s second annual virtual event for data and ML teams to discuss the practical data engineering challenges faced when building ML for the real world. There were talks on best practice development patterns, tools of choice, and emerging architectures to successfully build and manage production ML applications.

This long-form article dissects content from 14 sessions and lightning talks that I found most useful from attending apply(). These talks cover 3 major areas: industry trends, production use cases, and open-source libraries. Let’s dive in!

What I Learned From Attending Toronto Machine Learning Summit 2020

What I Learned From Attending Toronto Machine Learning Summit 2020

Last month, I had the opportunity to attend the Toronto Machine Learning Summit 2020, organized by the great people at the Toronto Machine Learning Society. I previously attended their MLOps event in the summer, which I also have written an in-depth recap here.

The summit aims to promote and encourage the adoption of successful machine learning initiatives within Canada and abroad. There was a variety of thought-provoking content tailored towards business leaders, practitioners, and researchers. In this long-form post, I would like to dissect content from the talks that I found most useful from attending the conference.

What I Learned From Attending #MLOPS2020 Production and Engineering World

What I Learned From Attending #MLOPS2020 Production and Engineering World

Two weeks ago, I attended the inaugural MLOps: Production and Engineering World, which is a two-day virtual conference organized by the Toronto Machine Learning Society that explores the best practices, methodologies, and principles of effective MLOps. In this post, I would like to share content from the talks that I attended during this conference.

Datacast Episode 27: Feature Engineering with Ben Fowler

Datacast Episode 27: Feature Engineering with Ben Fowler

Ben Fowler has been in the field of data science for over five years. In his current role at Southeast Toyota Finance, Ben leads the end to end model development process to solve the problem of interest. Ben holds a Master of Science in Data Science from Southern Methodist University, graduating in 2017. Following graduation, Ben has been a guest speaker to the SMU program multiple times. Additionally, Ben has spoken at the PyData Miami 2019 and PyData LA 2019 Conferences and has spoken multiple times at the West Palm Beach Data Science Meetup.