MLOps for Continuous Learning

MLOps empowers data scientists and app developers to help bring the machine learning models to production. MLOps enables you to track, version, audit, certify, reuse every asset in your machine learning lifecycle, and provides orchestration services to streamline managing this lifecycle. In this session, you will get inspired and learn how to bring together people, processes, and platform to automate machine learning-infused software delivery and also provide continuous value to your customers. Francesca Lazzeri Principal Data Scientist Manager at Microsoft Dr. Lazzeri is a data and machine learning scientist with over 15 years of experience in academic research, tech industry and engineering team management. She is author of the book “Machine Learning for Time Series Forecasting with Python” (Wiley) and many other publications, including technology journals and conferences. Francesca is Adjunct Professor of machine learning at Columbia University and Principal Data Scientist Manager at Microsoft, where she leads an organization of data scientists and machine learning engineers building intelligent applications on the Cloud, utilizing data and techniques spanning from IoT, time series forecasting, experimentation, causal inference, computer vision, natural language processing, reinforcement learning and open-source frameworks. Before joining Microsoft, she was a Research Fellow at Harvard University in the Technology and Operations Management Unit. She is also Advisory Board Member of the AI-CUBE (Artificial Intelligence and Big Data CSA for Process Industry Users, Business Development and Exploitation) project, the Women in Data Science (WiDS) initiative, machine learning mentor at the Massachusetts Institute of Technology, and active member of the AI community. You can find her on Twitter: https://twitter.com/frlazzeri and LinkedIn: https://www.linkedin.com/in/francescalazzeri/