Introduction to Building ML Microservices: A Hands-On Approach With Examples From The Music Industry скачать в хорошем качестве

Introduction to Building ML Microservices: A Hands-On Approach With Examples From The Music Industry

Speaker: Ramon Perez Developer Advocate, Seldon Abstract: Serving a machine learning model is not particularly easy, especially if we add two or three models in parallel to the mix, in which case, a single model deployment recipe might start to crumble. To tackle the challenges around serving individual or multiple models in production, we have handy tools like MLServer and Seldon Core. The former is a python library that allows us create machine learning microservices with one or multiple models in the same service, and the latter allows us to build simple-to-complex inference graphs that can help us handle A/B testing, shadow and canary deployment, feature transformations, and model monitoring. If you want to learn how to use open-source tools to build microservices based on your different use cases and model recipes, come and join this hands-on workshop and get started with several of the key steps in the machine learning workflow as we walk through fun examples from the broader music industry.