Just build it! Tips for making ML Engineering and MLOps Real
Data science and Machine Learning in an industrial setting are hard. The problems you have to solve are complex, the data landscape is challenging and you often don't have the freedom you would like to design experiments or create observational studies on real-world processes. This is before you even think about how to manage stakeholders, use cloud technologies, write software or wrap your solution up into a product that has to run predictions 24/7/365 and support business operations! In this talk, we reflect on many of the learnings Andy has gained through the past few years working in successful data science and machine learning engineering teams building operational products that create millions of dollars of value. In particular, Andy discusses how he thinks we can 'bootstrap' ML Engineering (MLEng) and MLOps practices in your organization.
Presenter - Andy McMahon
Machine Learning Engineering Lead , NatWest Group
Andy is a machine learning engineer and data scientist with experience of working in, and leading, successful analytics and software teams. His expertise centers on building production-grade ML systems that can deliver value at scale. Andy is currently an ML Engineering Lead at NatWest Group and was previously Analytics Team Lead at Aggreko. He has an undergraduate degree in theoretical physics from the University of Glasgow, as well as Masters and Ph.D. degrees in condensed matter physics from Imperial College London. In 2019, Andy was named Data Scientist of the Year at the International Data Science Awards. He currently co-hosts the AI Right podcast, discussing hot topics in AI with other members of the Scottish tech scene.
Rob Huggins, Director of Academy and Client Services at MBN Solutions | Data IQ 100 2019 & 2020 will be chairing the event.
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This is a group for anyone interested in Data Science, Big Data, Analytics and Technology trends. We started this group to build a community to discuss general insights into the market and share personal experiences of working and operating in this area. We hope to cover skills shortages, technological advancements and organisational implications in Data Science and Technology during our series of meetups. All skill levels are welcome.