Sep 23–26, 2019

Emily Webber
Machine Learning Specialist Solutions Architect, Amazon Web Services

Emily Webber is a machine learning specialist solutions architect at Amazon Web Services (AWS). She guides customers from project ideation to full deployment, focusing on Amazon SageMaker, where her customers are household names across the world, such as T-Mobile. She’s been leading data science projects for many years, piloting the application of machine learning into such diverse areas as social media violence detection, economic policy evaluation, computer vision, reinforcement learning, the IoT, drones, and robotic design. Previously, she was a data scientist at the Federal Reserve Bank of Chicago and a solutions architect for an explainable AI startup in Chicago. Her master’s degree is from the University of Chicago, where she developed new applications of machine learning for public policy research with the Data Science for Social Good Fellowship.

Sessions

1:30pm–5:00pm Tuesday, September 24, 2019

Location: 1A 21

Building a recommender system with Amazon ML services

Data Science, Machine Learning, & AI

Secondary topics: Cloud Platforms and SaaS, Deep dive into specific tools, platforms, or frameworks

Karthik Sonti (Amazon Web Services), Emily Webber (Amazon Web Services), Varun Rao Bhamidimarri (Amazon Web Services)

Karthik Sonti, Emily Webber, and Varun Rao Bhamidimarri introduce you to the Amazon SageMaker machine learning platform and provide a high-level discussion of recommender systems. You'll dig into different machine learning approaches for recommender systems, including common methods such as matrix factorization as well as newer embedding approaches. Read more.

5:25pm–6:05pm Wednesday, September 25, 2019

Location: 3B - Expo Hall

Alexa, do men talk too much?

Data Science, Machine Learning, & AI, Expo Hall

Secondary topics: Culture and Organization, Text and Language processing and analysis

Sireesha Muppala (Amazon Web Services), Shelbee Eigenbrode (Amazon Web Services), Emily Webber (Amazon Web Services)

Mansplaining. Know it? Hate it? Want to make it go away? Sireesha Muppala, Shelbee Eigenbrode, and Emily Webber tackle the problem of men talking over or down to women and its impact on career progression for women. They also demonstrate an Alexa skill that uses deep learning techniques on incoming audio feeds, examine ownership of the problem for women and men, and suggest helpful strategies. Read more.