PyData DC 2018

In the age of GDPR and its related lawsuits, the prevailing strategy of being indiscriminately “data greedy” to power opaque machine learning (ML) based products is not viable. In this talk, I’ll examine how ML and Data Science practitioners can balance principles of “data minimization & transparency” with delivering personalized and insightful products to their privacy conscious users.

Slides – https://drive.google.com/file/d/1PF5ILq_zub2McR2NRM6psbjauQNAy00-/view?usp=sharing
===
www.pydata.org

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome!
00:10 Help us add time stamps or captions to this video! See the description for details.

Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVideoTimestamps

source