Kenny Daniel - DevOps for ML and other Half-Truths: Processes and Tools for the ML Lifecycle

- Speaker Bio -
Kenny Daniel is a founder and CTO of Algorithmia. He came up with the idea for Algorithmia while working on his PhD and seeing the plethora of algorithms that never saw the light of day.
In response, he built the Algorithmia Cloud AI Layer, which has helped more than 80,000 developers share, pipeline, and consume more than 7000 models. Through his work with hundreds of companies implementing ML, he then created the Enterprise AI Layer, which helps the largest organizations in the world deploy, connect, manage, and secure machine learning operations at scale.
Kenny holds degrees from Carnegie Mellon University and the University of Southern California, where he studied artificial intelligence and mechanism design.
- Talk Abstract -
Traditional software development has a Software Development Life Cycle, coalesced around a set of tools and processes. In contrast, machine learning is a tangle of tools, languages, and infrastructures, with almost no standardization.
To build and deploy enterprise-ready machine learning models that generate real value, organizations need to consider a standard ML focused life cycle that supports IT’s Operations Management and Infrastructure groups.