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I love this—it’s a fascinating look behind the scenes at Airbnb, where they are conquering some of the thorniest problems associated with scaling data science teams; something I’ve been thinking a lot about recently. Their answer: scale by building tooling that creates consistency and leverage for their data scientists.
Microservices and containerization both provide interesting commercial opportunities for algorithms. Today, most algorithms are tightly coupled with the software and data within a given company. This post proposes a different, more composable, future.
Ever since the AlphaGo victory, I’ve been hearing about the innovative moves it used to defeat the staid human playing style of Lee Sedol. This Quartz article does a great job of explaining (to non-Go players!) what moves the AI made, why they were unpredictable, and when they did and did not work. The qualitative difference between human and artificial intelligence takes center stage here.
There have been plenty of voices in the past month expressing opinions on one question: what does AlphaGo’s victory mean? Can human-level artificial general intelligence be achieved with current techniques? Some say yes, others say no.
Data science teams are new, and the thinking around how best to run such a team is evolving quickly. Erik Andrejko, who runs just such a team, shares his thinking on this topic, answering questions like “How do we trust each others’ work?”, “Where should we sit within the organization?”, and “What processes should we use?” MUST READ
This post from the McKinsey Global Institute points out that the focus of the high school math curriculum on calculus doesn’t reflect current workforce realities. Statistics and linear algebra are much more relevant to the knowledge worker of the 21st century. If there are any math teachers reading this, I’d love to hear what you think.
For any readers in NYC, we’d love to have you at our Meetup, April 14th. We’ll be talking to data scientists and analysts from around the city. You can sign up at the link; looking forward to seeing you there!
Quote of the Week
“Humans understand and communicate uncertainty with stories; reasoning from cases and examples. Probabilistic programming enables computers to do the same. “
Each week we surface, summarize, and share the most interesting stories and biggest news from the world of data science. Have articles or podcasts that you think we should be covering in our Data Science Roundup? Send them to email@example.com.
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