Presentation: How to Make Great Personalization Private

Track: Deep Learning in Practice

Location: Embarcadero

Duration: 1:20pm - 2:00pm

Day of week: Tuesday

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Abstract

Canopy is a privacy startup that believes that users should not have to give up their personal data in order to get good recommendations. And we're building a content discovery app to prove it. Come learn what a private recommendation stack looks like in 2019, and how to tackle issues like analytics, models updates and algorithmic fairness in a world where you want to know as little about your users as possible. 

Speaker: Erica Greene

Machine Learning Engineer @ourcanopy

Erica Greene is a machine learning engineer at a privacy startup called Canopy. She is building a private recommendation system that will allow people to find delightful content online without giving up their personal data. Erica previously worked as an engineer and manager at The New York Times where she ran a project to roll out algorithmic comment moderation across the site.  She is passionate about increasing diversity in tech, and has spent a lot of time developing programs and policies that support women and other underrepresented groups.

Find Erica Greene at

2019 Tracks

  • Groking Timeseries & Sequential Data

    Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.

  • Deep Learning in Practice

    Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.