Machine Learning Operations Frameworks with MaRS and Amazon Web Services

MaRS Discovery District(@MaRSDD) helps Canadian startups succeed so they can solve our toughest problems in such areas as climate, health and the economy. As North America’s largest urban innovation hub and a registered charity, MaRS provides direct support to more than 1,200 ventures, builds communities of innovators within its 1.5-million square feet of lab and office space, and spurs the adoption of new solutions — in Canada and around the world.

MaRS Discovery District

Learn how to manage ML workloads in the cloud from some of AWS’s leading tech experts. 

This November 12, you’re invited to our first MaRS and AWS ML/AI Initiative workshop, this time focused on machine learning operations (MLOps) frameworks in the cloud.In this session, we discuss how best practices (established by AWS Well-Architected) apply to ML workloads, as well as key distinctions between the unique nature of ML architecture and other systems. <h3>DETAILS</h3>November 19, 202011:00 a.m. ESTZoom broadcast<h3>WHO SHOULD ATTEND</h3>Founders and engineers from invited startups in the MaRS portfolio<h3>ABOUT THE SPEAKERS</h3>

Mohsen Ansari, solutions builder, AWSMohsen works with AWS customers to identify and build ML solutions to address their highest return-on-investment ML opportunities. For nearly a decade, he’s been developing software products for large enterprises like Telus and Deloitte, as well as for scaling startups, and is an expert in the latest AI/ML software development methodologies.

Johny Duval, product manager, AI/ML, AWSJohny leads a team of solutions builders in bringing to market end-to-end products leveraging AI technologies in the fields of machine learning, natural language processing, speech, vision and planning. After many years leading startup teams of various sizes through different stages (including Element AI and Sweet IQ), Johny has accumulated countless hours of experience formulating strategy, getting tech companies through product-market fit, scaling and capitalization. He understands the value of empathy in product development — that is, deeply understanding customer pain points and building solutions to provide genuine value.

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Machine Learning Operations Frameworks with MaRS and Amazon Web Services

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