Conference

What I Learned From Attending REWORK MLOps and ML Fairness Summits

What I Learned From Attending REWORK MLOps and ML Fairness Summits

Last month, I attended two great summits organized by REWORK: The MLOps summit that discovers how to optimize the ML lifecycle & streamline ML pipeline for better production and the ML Fairness summit that discovers strategies to ensure ML models are accountable & fair to build secure & responsible AI. As a previous attendee of REWORK’s in-person summit, I have always enjoyed the unique mix of academia and industry, enabling attendees to meet with AI pioneers at the forefront of research and explore real-world case studies to discover the business value of AI.

In this long-form blog recap, I will dissect content from the talks that I found most useful from attending the summit. The post consists of 10 talks that range from automated data labeling and pipeline optimization, to model fairness and responsible AI at scale.

What I Learned From Attending REWORK AI Applications Summit 2021

What I Learned From Attending REWORK AI Applications Summit 2021

Last month, I attended REWORK’s AI Applications Virtual Summit, which discovers machine learning tools and techniques to improve the financial, retail, and insurance experience. As a previous attendee of REWORK’s in-person summit, I have always enjoyed the unique mix of academia and industry, enabling attendees to meet with AI pioneers at the forefront of research and explore real-world case studies to discover the business value of AI.

In this long-form blog recap, I will dissect content from the talks that I found most useful from attending the summit. The post consists of 13 talks that are divided into 3 sections: (1) AI in Finance and RegTech, (2) AI in Retail and Marketing, and (3) AI in Insurance.

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

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

Last week, I attended apply(), Tecton’s first-ever conference that brought together industry thought leaders and practitioners from over 30 organizations to share and discuss ML data engineering’s current and future state. The complexity of ML data engineering is the most significant barrier between most data teams and transforming their applications and user experiences with operational ML.


In this long-form blog recap, I will dissect content from 23 sessions and lightning talks that I found most useful from attending apply(). These talks cover everything from the rise of feature stores and the evolution of MLOps, to novel techniques and scalable platform design. Let’s dive in!

What I Learned From Attending Scale Transform 2021

What I Learned From Attending Scale Transform 2021

A few weeks ago, I attended Transform, Scale AI’s first-ever conference that brought together an all-star line-up of the leading AI researchers and practitioners. The conference featured 19 sessions discussing the latest research breakthroughs and real-world impact across industries.

In this long-form blog recap, I will dissect content from the session talks that I found most useful from attending the conference. These talks cover everything from the future of ML frameworks and the importance of a data-centric mindset to AI applications at companies like Facebook and DoorDash. To be honest, the conference's quality was so amazing, and it’s hard to choose the talks to recap.

What I Learned From Attending DataOps Unleashed 2021

What I Learned From Attending DataOps Unleashed 2021

Last week, I attended DataOps Unleashed, a great event that examines the emergence of DataOps, CloudOps, AIOps, and other professionals coming together to aggregate conversations around the latest trends and best practices for running, managing, and monitoring data pipelines.

This long-form blog recap dissects content from the session talks that I found most useful from attending the summit. These talks are from DataOps professionals at leading organizations detailing how they establish data predictability, increase reliability, and create economic efficiencies with their data pipelines.

What I Learned From Attending RE•WORK Deep Learning 2.0 Summit 2021

What I Learned From Attending RE•WORK Deep Learning 2.0 Summit 2021

At the end of January, I attended REWORK’s Deep Learning 2.0 Virtual Summit, which brings together the latest technological advancements and practical examples to apply deep learning to solve challenges in business and society. In this long-form blog recap, I will dissect content from the talks that I found most useful from attending the summit. The post consists of 17 talks that are divided into 5 sections: Enterprise AI, Ethics and Social Responsibility, Deep Learning Landscape, Generative Models, and Reinforcement Learning.

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 #SparkAISummit 2020

What I Learned From Attending #SparkAISummit 2020

One of the best virtual conferences that I attended over the summer is Spark + AI Summit 2020, which delivers a one-stop-shop for developers, data scientists, and tech executives seeking to apply the best data and AI tools to build innovative products. I learned a ton of practical knowledge: new developments in Apache Spark, Delta Lake, and MLflow; best practices to manage the ML lifecycle, tips for building reliable data pipelines at scale; latest advancements in popular frameworks; and real-world use cases for AI.

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.