Challenges in Deploying and Monitoring Machine Learning Systems

Alessandra Tosi · Andrei Paleyes · Christian Cabrera · Fariba Yousefi · S Roberts



he goal of this event is to bring together people from different communities with the common interest in the Deployment of Machine Learning Systems.

With the dramatic rise of companies dedicated to providing Machine Learning software-as-a-service tools, Machine Learning has become a tool for solving real world problems that is increasingly more accessible in many industrial and social sectors. With the growth in number of deployments, also grows the number of known challenges and hurdles that practitioners face along the deployment process to ensure the continual delivery of good performance from deployed Machine Learning systems. Such challenges can lie in adoption of ML algorithms to concrete use cases, discovery and quality of data, maintenance of production ML systems, as well as ethics.

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