The rise of big data and responding to COVID-19 with Roger and DJ
Listen now
Roger and DJ share some of the history behind data science as we know it today, and reflect on their experiences working on California's COVID-19 response. --- Roger Magoulas is Senior Director of Data Strategy at Astronomer, where he works on data infrastructure, analytics, and community development. Previously, he was VP of Research at O'Reilly and co-chair of O'Reilly's Strata Data and AI Conference. DJ Patil is a board member and former CTO of Devoted Health, a healthcare company for seniors. He was also Chief Data Scientist under the Obama administration and the Head of Data Science at LinkedIn. Roger and DJ recently volunteered for the California COVID-19 response, and worked with data to understand case counts, bed capacities and the impact of intervention. Connect with Roger and DJ: 📍 Roger's Twitter: 📍 DJ's Twitter: --- 🌟 Transcript: 🌟 ⏳ Timestamps: 0:00 Sneak peek, intro 1:03 Coining the terms "big data" and "data scientist" 7:12 The rise of data science teams 15:28 Big Data, Hadoop, and Spark 23:10 The importance of using the right tools 29:20 BLUF: Bottom Line Up Front 34:44 California's COVID response 41:21 The human aspects of responding to COVID 48:33 Reflecting on the impact of COVID interventions 57:06 Advice on doing meaningful data science work 1:04:18 Outro 🍀 Links: 1. "MapReduce: Simplified Data Processing on Large Clusters" (Dean and Ghemawat, 2004): 2. "Big Data: Technologies and Techniques for Large-Scale Data" (Magoulas and Lorica, 2009): 3. The O'RLY book covers: 4. "The Premonition" (Lewis, 2021): 5. Why California's beaches are glowing with bioluminescence: 6. 7. Sturgis Motorcyle Rally: --- Get our podcast on these platforms: 👉 Apple Podcasts:​​ 👉 Spotify:​ 👉 Google Podcasts:​​ 👉 YouTube:​​ 👉 Soundcloud:​ Join our community of ML practitioners where we host AMAs, share interesting projects and meet other people working in Deep Learning:​​ Check out Fully Connected, which features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, industry leaders sharing best practices, and more:
More Episodes
In this episode, Emily and Lukas dive into the problems with bigger and bigger language models, the difference between form and meaning, the limits of benchmarks, and why it's important to name the languages we study. Show notes (links to papers and transcript):...
Published 09/09/21
Jeff talks about building Facebook's early data team, founding Cloudera, and transitioning into biomedicine with Hammer Lab and Related Sciences.
Published 08/26/21
Josh explains how astronomy and machine learning have informed each other, their current limitations, and where their intersection goes from here. --- Josh is a Professor of Astronomy and Chair of the Astronomy Department at UC Berkeley. His research interests include the intersection of...
Published 08/20/21