Get insights on the main problems companies are facing when developing and deploying ML models and what improvements do companies expect from the introduction of DataOps/MLOps.
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Artificial intelligence (AI), machine learning (ML) and data science are among a large group of buzzwords associated with major breakthroughs in the way business is done and better outcomes are achieved. Therefore it is of importance to examine the mechanisms behind those success stories and the methods that come into play to achieve them, focusing specifically on the concepts of DataOps and MLOps and their impact on the application of ML.
In this global survey, we examined the main problems companies are facing when developing and deploying ML models and what improvements do companies expect from the introduction of DataOps/MLOps. Watch our webinar on the study and hear the views of BARC analysts and software vendors on the results of the study.
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