O’Reilly Radar: Data and AI

Free online event

Oct 14, 7:00am–10:30am PT/10:00am–1:30pm ET/4:00pm–7:30pm CET

Registration is closed for this event.

O’Reilly Radar: Data & AI will showcase what’s new, what’s important, and what’s coming in the field. It includes two keynotes and two concurrent three-hour tracks—designed to lay out for tech leaders the issues, tools, and best practices that are critical to an organization at any step of their data and AI journey. You’ll explore everything from prototyping and pipelines to deployment and DevOps to responsible and ethical AI.

This is a great opportunity to get an insider’s view of where data and AI are going—and how to get there first. It’s free to attend, but reservations are required. Save your spot now.

This event will be held again on October 21 for those in the Asia-Pacific time zones. Get more info here.


7:00am PT/10:00am ET/4:00pm CET

Data and AI Trends: What You and Your Team Need to Know to Successfully Innovate

Rachel Roumeliotis, VP of data and AI content at O’Reilly, will present our latest findings on data and AI adoption.


7:20am PT/10:20am ET/4:20pm CET

AI in Healthcare: Where It Helps—and Where It Doesn’t

Jeremy Howard, founding researcher at fast.ai, distinguished research scientist at the University of San Francisco, the chair of WAMRI, and chief scientist at Platform.ai, will discuss AI in healthcare: where it helps—and where it doesn’t.

7:40am PT/10:40am ET/4:40pm CET

How to Keep Up with ML: What Can You Do to Avoid Being Left Behind?

Aurélien Géron, author of Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, second edition, will explain how to best absorb the concepts about machine learning—and how to keep up with the continually evolving topic.

AI Track

Hosted by Shingai Manjengwa

8:05am PT/11:05am ET/5:05pm CET

What’s Still Missing from the Responsible AI Movement

Aileen Nielsen, Fellow in Law and Technology at ETH Zurich and Author of Practical Time Series Analysis and Practical Fairness

8:35am PT/11:35am ET/5:35pm CET

MLOps from Zero to One

Noah Gift, Lecturer at UC Davis and Northwestern and Author of Practical MLOps: Operationalizing ML Models

9:10am PT/12:10pm ET/6:10pm CET

NeuralQA: A Usable Library for Question Answering on Large Datasets Using BERT-Based Models

Victor Dibia, Research Engineer in Machine Learning at Cloudera Fast Forward Labs

9:40am PT/12:40pm ET/6:40pm CET

Demystifying Scalable Machine Learning with the Spark Ecosystem

Adi Polak, Senior Software Engineer and Developer Advocate at Microsoft and Author of the Upcoming Book Machine Learning with Apache Spark

Data Track

Hosted by Theresa Johnson

8:05am PT/11:05am ET/5:05pm CET

Prototype to Pipeline: Evolving from Data Exploration to Automated Data Processing

Sev Leonard, Senior Software Engineer at Fletch

8:45am PT/11:45am ET/5:45pm CET

Watch Me Learn: Querying Data the Right Way

Vinoo Ganesh, Head of Business Engineering at Ashler Capital at Citadel

9:10am PT/12:10pm ET/6:10pm CET

Improving Data Quality with a Focus on Data Reliability and Observability

Barr Moses, Cofounder and CEO at Monte Carlo

9:40am PT/12:40pm ET/6:40pm CET

Train and Predict with Amazon Redshift ML Using SQL

Chris Fregly, Developer Advocate for AI and Machine Learning at Amazon Web Services

Antje Barth, Senior Developer Advocate for AI and Machine Learning at Amazon Web Services

Closing Address

10:10am PT/1:10pm ET/7:10pm CET

The Future of Data and AI

Tim O’Reilly, O’Reilly’s founder and CEO, will share his perspectives on the biggest challenges we face in data and AI, the most promising approaches to solving them, and the new market opportunities that are opening up for entrepreneurs and existing businesses.