Dev Ops for Data Science

In this episode, Kyle Polich sits down with Cory Zechmann, a content curator working in streaming television with 16 years of experience running the music blog "Silence Nogood." They explore the intersection of human curation and machine learning in content discovery, discussing ...  Show more

In this episode, Santiago de Leon takes us deep into the world of eye tracking and its revolutionary applications in recommender systems. As a researcher at the Kempelin Institute and Brno University, Santiago explains the mechanics of eye tracking technology—how it captures gaze ...  Show more

"DevOps is dead."

Well, not exactly. But the DevOps methodology of "you build it, you run it" has been failing development teams for years.

On this week's episode of Dev Interrupted, we sit down with Kaspar von Grünberg, founder & ...

Data scientists and engineers don’t always play well together. Data scientists will plan out a solution, carefully build models, test them in notebooks, then throw that solution over the wall to engineering. Implementing that solution can take months.

Historically, the d ...

Matt Stratton beams aboard the Datanauts starship to share his opinions and experiences with DevOps. Is DevOps a role you can hire for, or a culture you create? If it's the later, how do you get started, what are the impacts, and how do you iterate? The post Datanauts 166: Can Yo ...  Show more

As the race to deliver applications ramps up, the wall between development and operations comes crashing down. When it does, those on both sides learn to work together like never before. But what is DevOps, really? Developer guests, including Microsoft’s Scott Hanselman and Cindy ...  Show more