In this episode of the Data Show, I spoke Jesse Anderson, managing director of the Big Data Institute, and my colleague Paco Nathan, who recently became co-chair of Jupytercon. This conversation grew out of a recent email thread the three of us had on machine learning engineers, a new job role that LinkedIn recently pegged as the fastest growing job in the U.S. In our email discussion, there was some disagreement on whether such a specialized job role/title was needed in the first place. As Eric Colson pointed out in his beautiful keynote at Strata Data San Jose, when done too soon, creating specialized roles can slow down your data team.

We recorded this conversation at Strata San Jose, while Anderson was in the middle of teaching his very popular two-day training course on real-time systems. We closed the conversation with Anderson’s take on Apache Pulsar, a very impressive new messaging system that is starting to gain fans among data engineers.

What Machine Learning Engineers Need to Know

O'Reilly Media spreads the knowledge of innovators. At O’Reilly, a big part of our business is paying attention to what’s new and interesting in the world of technology. We have a pretty good record at having anticipated some of the big technology developments in recent history. For instance, we launched the first commercial Web site, GNN, in 1993; we organized the meeting at which the term “open source” was first adopted; we were early investors in Blogger, which helped launch the blogging revolution; and more recently, our Web 2.0 conference launched a world-wide meme. We call this predictive sense the “O’Reilly Radar.” And while we’re certainly not always right, we are, at least, good at making interesting guesses.

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What Machine Learning Engineers Need to Know

O'Reilly Radar