Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK
Francesca Lazzeri

Francesca Lazzeri
Senior Machine Learning Scientist, Microsoft

Website | @frlazzeri

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.


9:0012:30 Tuesday, 30 April 2019
Data Science, Machine Learning & AI
Location: Capital Suite 15
Holden Karau (Independent), Trevor Grant (IBM), Francesca Lazzeri (Microsoft)
Average rating: ****.
(4.43, 7 ratings)
Holden Karau, Francesca Lazzeri, and Trevor Grant offer an overview of Kubeflow and walk you through using it to train and serve models across different cloud environments (and on-premises). You'll use a script to do the initial setup work, so you can jump (almost) straight into training a model on one cloud and then look at how to set up serving in another cluster/cloud. Read more.
13:3017:00 Tuesday, 30 April 2019
Data Science, Machine Learning & AI
Location: Capital Suite 2/3
Francesca Lazzeri (Microsoft), Aashish Bhateja (Microsoft)
Average rating: ****.
(4.25, 4 ratings)
Time series modeling and forecasting is fundamentally important to various practical domains; in the past few decades, machine learning model-based forecasting has become very popular in both private and public decision-making processes. Francesca Lazzeri walks you through using Azure Machine Learning to build and deploy your time series forecasting models. Read more.