Li Rong

Who are the MLOps in Yelp: from prototype to production

Machine Learning is a field which continues to grow, it is used pretty much everywhere, from image recognition to fraud detection to item recommendations to protein structure predictions. And what do these tasks have in common? To accomplish them, they all require robust machine learning models which need to be trained, tested and served. In this session we will be discussing having a dedicated ops team for this: MLOps. Who are the MLOps in Yelp? How do they differ from DevOps? And how building a horizontal layer of support across teams and providing infrastructure for experimentation, testing, training, model serving, data storage and everything in between can make a huge difference to the efficiency and quality of life of Machine Learning teams within Yelp. We will dive into details about how Yelp prototype ML projects and bring them into production with the help of MLOps to power thousands of small businesses.

Li is an engineer currently in the Core-ml team(Applied Machine Learning group) . Li was training for a career in the dance industry until the pandemic hit, when Li went back to software engineering and specialized in Machine Learning and Artificial Intelligence. Before that Li has worked across stacks in various companies, including Goldman Sachs, Skyscanner, Transferwise, just to name a few. Li was also a coding instructor for the non-profit "Code First Girls".

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