Abstract
This paper is an overview of the Machine Learning Operations (MLOps) area. Our aim is to de?ne the operation and the components of such systems by highlighting the current problems and trends. In this context we present the different tools and their usefulness in order to provide the corresponding guidelines. Machine learning operations (MLOps) is quickly becoming a critical component of successful data science project deployment in the enterprise. It’s a process that helps organisations and business leaders generate long-term value and reduce risk associated with data science, machine learning, and AI initiatives. Yet it’s a relatively new concept; so why has it seemingly skyrocketed into the data science lexicon overnight? This introductory chapter delves into what MLOps is at a high level, its challenges, why it has become essential to a successful data science strategy in the enterprise, and, critically, why it is coming to the forefront now.
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