Francesca Lazzeri
Senior Machine Learning Scientist, Microsoft

Francesca Lazzeri is a senior machine learning scientist at Microsoft on the cloud advocacy team and an expert in big data technology innovations and the applications of machine learning-based solutions to real-world problems. Her research has spanned the areas of machine learning, statistical modeling, time series econometrics and forecasting, and a range of industries—energy, oil and gas, retail, aerospace, healthcare, and professional services. Previously, she was a research fellow in business economics at Harvard Business School, where she performed statistical and econometric analysis within the technology and operations management unit. At Harvard, she worked on multiple patent, publication and social network data-driven projects to investigate and measure the impact of external knowledge networks on companies’ competitiveness and innovation. Francesca periodically teaches applied analytics and machine learning classes at universities and research institutions around the world. She’s a data science mentor for PhD and postdoc students at the Massachusetts Institute of Technology and speaker at academic and industry conferences—where she shares her knowledge and passion for AI, machine learning, and coding.

Sessions

11:05am–11:45am Thursday, September 12, 2019

Location: Expo Hall 3

Using automated machine learning for hyperparameter optimization and algorithm selection

Models and Methods

Secondary topics: Machine Learning, Temporal data and time-series

Francesca Lazzeri (Microsoft)

Average rating:

(3.50, 2 ratings)

Automated machine learning (AutoML) enables data scientists and domain experts to be productive and efficient. AutoML is seen as a fundamental shift in the way in which organizations can approach machine learning. Francesca Lazzeri outlines how to use AutoML to automate machine learning model selection and hyperparameter tuning. Read more.