The O’Reilly Data Show Podcast: Andrew Feldman on why deep learning is ushering a golden age for compute architecture.
While models and algorithms garner most of the media coverage, this is a great time to be thinking about building tools in data.
Oaths have their value, but checklists will help put principles into practice.
An overview of the challenges MLflow tackles and a primer on how to get started.
Taking blockchain technology private for the enterprise.
The two positions are not interchangeable—and misperceptions of their roles can hurt teams and compromise productivity.
Why model development does not equal software development.
Data scientists, data engineers, AI and ML developers, and other data professionals need to live ethical values, not just talk about them.
Get intensive, hands-on training on current critical data technology topics, led by instructors from O'Reilly's unparalleled network of tech innovators and expert practitioners.
Working with uncertainty in real-world data.
The adventures in deep learning and cheap hardware continue!
“Data is having an impact on business models and profitability. It’s hard to find a non-trivial application that doesn’t use data in a significant manner.”— Ben Lorica, Director of Content Strategy for Data at O'Reilly Media