Deloitte June 24, 2021
Scaling model development and operations with a dose of engineering and operational discipline
The era of artisanal AI must give way to MLOps—the application of engineering discipline to automate ML model development, maintenance, and delivery—to shorten development life cycles and industrialize AI.
Sophisticated machine learning models help organizations efficiently discover patterns, reveal anomalies, make predictions and decisions, and generate insights; Forrester reports that more than half of global data and analytics technology decision-makers have implemented or are in the process of implementing some form of AI.1 As machine learning and AI increasingly become key drivers of organizational performance, enterprises are realizing the need to shift from personal heroics...
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