The past two years I have conducted an extensive literature and tool review to answer the question: “What should software engineers learn about building production-ready machine learning systems?”. During my research I noted that because the discipline of building production-ready machine learning systems is so new, it is not so easy to get the terminology straight. People write about it from different perspectives and backgrounds and have not yet found each other to join forces. At the same time the field is moving fast and far from mature. My focus on material that is ready to be used with our bachelor level students (applied software engineers, profession-oriented education), helped me to consolidate everything I have found into a body of knowledge for building production-ready machine learning (ML) systems. In this post I will first define the discipline and introduce the terminology for AI engineering and MLOps.
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This research investigates the impact of early facility management involvement on the effective utilization of building information modelling during the operation and maintenance phase. It looks at understanding the factors that encourage building owners to prioritize early facility manager engagement. This research also examined the role of facility managers when involved early in the process, including the stage in which FM should be involved, the additional knowledge and competencies to add value, the main tasks to perform and what barriers should be overcome to involve FM early. Lastly, this research defines the potential added value that early engagement has on the use of BIM in the operational phase. Recognizing that facility managers bear the ultimate responsibility for building management, this study explores how their early engagement can ensure BIM model align with operational needs, maximizing the technology’s benefits throughout a building’s lifespan. By examining the impact of early FM input, this research aims to provide actionable insights for facility managers to contribute to the BIM development process.
MULTIFILE
Er is een toename van het aanbod van e-health-toepassingen in Nederland, dat blijkt onder meer uit de e-health monitor 2016 (www.e-health-monitor.nl). Eén van de aanbevelingen uit deze monitor is dat meer onderzoek moet plaatsvinden naar veilige en effectieve e-health-toepassingen. In dit artikel bundelen onderzoekers van verschillende kenniscentra hun ervaringen en beschrijven de door hen geleerde lessen die zijn gebaseerd op diverse onderzoeksprojecten.
