Automated Machine Learning on Azure

Automated machine learning, also referred to as automated ML or AutoML, is the process of automating the time consuming, iterative tasks of machine learning model development. It allows data scientists, analysts, and developers to build ML models with high scale, efficiency, and productivity all while sustaining model quality. Automated ML in Azure Machine Learning is based on a breakthrough from our Microsoft Research division.

Who is it aimed at?
Students who want to pursue a career in data science and machine learning.

Why should I attend?
Traditional machine learning model development is resource-intensive, requiring significant domain knowledge and time to produce and compare dozens of models. With automated machine learning, you'll accelerate the time it takes to get production-ready ML models with great ease and efficiency.

Speaker bio: Francesca Lazzeri, PhD is an experienced scientist and machine learning practitioner with over 12 years of both academic and industry experience. She is author of “Machine Learning for Time Series Forecasting” book (Wiley) and many other publications, including technology journals and conferences.
Francesca is Adjunct Professor of AI and machine learning at Columbia University and Principal Cloud Advocate Manager at Microsoft, where she leads an international team (across USA, Canada, UK and Russia) of cloud AI developer advocates and engineers, managing a large portfolio of customers in the research/academic/education sector and building intelligent automated solutions on the cloud.
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 Women in Data Science (WiDS) initiative, machine learning mentor at the Massachusetts Institute of Technology and Columbia University, and active member of the AI community.

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