ODSC East 2022 surprises included how often "confident" data models are right (and wrong), and the extent to which humans in the loop affect outcomes.
Keith McCormick
Humans are necessary while automating decisions and processes with AI, machine learning, and RPA. Experts discuss the need for humans in the loop (HITL).
Learn how CloudFactory’s managed workforce worked with 3 companies, each with a problem involving data, automation, and/or ML.
An incremental design approach to automation and machine learning affords strategic opportunities for choosing to route exceptions to machines or people.
Automation and AI hold great potential to innovate, improve, and make predictions. Here are three mistakes you’ll want to avoid.
Could the secret to developing ML be more boring than we think? It’s time to give up the quest for the perfect model.
