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Why ML Projects Fail and How to Ensure Their Success

Recent Gartner research pegged the failure rate of data and AI projects at 60-85%. There are many reasons why AI projects fail, but the question remains: What can leaders do to increase the success rate of ML/AI projects? This panel discussion will explore the principles, processes and practices that allow teams to get more models, with greater impact, launched and into production more quickly and consistently.