Radar Talks: Hugo Bowne-Anderson on MLOps Versus DevOps
Published by O'Reilly Media, Inc.
Why data makes it different
There’s a pressing need for tools and workflows that meet data scientists where they are. This is also a serious business need: how to enable an organization of data scientists, who aren’t software engineers by training, to build and deploy end-to-end machine learning workflows and applications independently. The new category of tools, frameworks, and processes that fill this need is often called MLOps.
Join us for this edition of Radar Talks with Hugo Bowne-Anderson to learn why machine learning applications need special treatment in the first place and why we can’t just fold them into existing DevOps best practices. You’ll also explore what a modern technology stack for streamlined ML processes looks like and discover how you can start applying the stack in practice today.
The O’Reilly Radar Talks series brings you expert opinions on emerging topics through hour-long interactive events. In conversation with some of the industry’s top minds, you’ll look at the early signals indicating significant trends and new technologies that will shape the future—and discover how to begin forging these technologies now. Share your own predictions and ask your questions while gaining insight into our experts’ unique outlooks for the future.
What you’ll learn and how you can apply it
- Understand why machine learning applications require special treatment
- Discover what a modern technology stack for streamlined ML processes looks like
- Learn how to start applying the stack in practice today
This live event is for you because...
- You want to learn about emerging technologies and their projected impact on the future of the industry.
- You want to know about the fundamentals of machine learning as an engineering discipline, learn how to embed scientific data-driven applications into business systems, and see which directions the industry is heading.
Prerequisites
- Come with your questions for Hugo Bowne-Anderson
- Have a pen and paper handy to capture notes, insights, and inspiration
Recommended follow-up:
- Read Effective Data Science Infrastructure (book)
- Read Practical MLOps (book)
- Read Introducing MLOps (book)
- Read What Is MLOps? (report)
- Take Practical MLOps (live online training course with Noah Gift)
Schedule
The time frames are only estimates and may vary according to how the class is progressing.
Tuesday, April 5, 2022, at 3pm PT / 6pm ET
- Introduction and presentation (15 minutes)
- Interactive discussion and Q&A (45 minutes)
Your Guest
Hugo Bowne-Anderson
Hugo Bowne-Anderson is an independent data and AI consultant with extensive experience in the tech industry. He’s the host of the podcast Vanishing Gradients, where he explores cutting-edge developments in data science and artificial intelligence. As a data scientist, educator, evangelist, content marketer, and strategist, Hugo has worked with leading companies in the field. His past roles include head of developer relations at Outerbounds, a company committed to building infrastructure for machine learning applications, and positions at Coiled and DataCamp, where he focused on scaling data science and online education respectively. Hugo's teaching experience spans from institutions like Yale University and Cold Spring Harbor Laboratory to conferences such as SciPy, PyCon, and ODSC. He has also worked with organizations like Data Carpentry to promote data literacy. His impact on data science education is significant, having developed over 30 courses on the DataCamp platform that have reached more than 3 million learners worldwide. Hugo also created and hosted the popular weekly data industry podcast DataFramed for two years. Committed to democratizing data skills and access to data science tools, Hugo advocates for open source software both for individuals and enterprises.