Towards Cloud Native Data Science

In my talk at ODSC West I wanted to start a conversation about what if any value the idea of Cloud Native Applications has for data science. The video and slides from my presentation are below and the slides are also available without speaker notes.

If you haven’t heard of Cloud Native Applications, the idea is to write applications that take full advantage of the benefits of cloud deployment and understand the limitations and constraints of the platform.
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ODSC West Day Two

After a great first day, ODSC West started up again on a blustery Sunday morning in the Bay Area. As I needed to prepare for my own talk I didn’t get to see as many of the other sessions as I would have liked, but I’ve collected some thoughts on those that I did see.

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ODSC West Day One

ODSCI’m out in San Francisco for the first time in months, to speak at the first Bay Area edition of the Open Data Science Conference. For a relatively new conference there is a great line-up of speakers and the audience is already quite big with around 1000 data scientists attending.
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CF Summit Talk on Data Science

A few weeks ago I was able to attend this year’s Cloud Foundry Summit, the conference for all things Cloud Foundry in Santa Clara, California. The event was a great success with lots of interesting talks from developers, operators and customers of CF, and the organisation of the conference itself was splendid, including one of the best exhibition halls I’ve seen, complete with ping pong tables, arcade games and delicious food.
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Data Science & XP Explained: Practices

In the previous two posts in this series we have explored the values and principles outlined in Extreme Programming Explained by Kent Beck and Cynthia Anders (XP Explained). In this post we will discuss perhaps the most contentious of the three layers: practices.

What relevance do XP practices have for data scientists? What are the benefits and disadvantages of these practices? Are there any that we should modify for a data science environment?

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