Some Things I Wish I Had Known About Scaling Machine Learning Solutions

Session
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Building artificial solutions in the real world is a road full of challenges and very few answers. From training, regularization to deployment and monitoring we are just starting to figure out what are the best practices used to build AI solutions at scale.
This session presents a series of patterns and anti-patterns of large scale AI solutions. Covering the entire lifecycle of AI solutions, from training to deployment, we will explore patterns and architectures that should be followed to build AI solutions at scale as well as not-so-obvious anti-patterns that can result in major disasters. To keep things practical, we will explore our AI patterns and anti-patterns through the lens of real customers building real AI solutions.

Behind the Tracks