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.
Welcome
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.
Keynotes
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.
