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Friday, October 22, 2021

Improving Data Science ROI using ML Ops
Karl Schelhammer
Karl Schelhammer
Slalom, Principal Data Scientist

Artificial Intelligence and Machine Learning are key technologies that can help companies build new capabilities, access new markets, and improve operations. The challenge to modern companies is not just learning to leverage AI/ML, but to do so in a way that reliably converts effort to business value. Having seen first-hand the challenges and solutions associated with AI/ML, I can attest to the benefit of grounding this effort in a foundation of best practices. ML Ops is a relatively new take on emerging trends in software engineering and dev ops, adapted for data scientists, that simplifies and streamlines ways of working with AI/ML. Cloud platforms like AWS provide a wide array of tools that make this easy. In this presentation, I will describe the typical struggles most organizations have with AI/ML and chart a way forward that any company can use to start improving their ROI on advanced AI/ML initiatives.