Category: Data Science
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Extending GraphLab to tables
The popular graph analytics framework extends its coverage of the data science workflow [A version of this post appears on the O’Reilly Data blog and Forbes.] GraphLab’s SFrame, an interesting and somewhat under-the-radar tool was unveiled1…
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Bridging the gap between research and implementation
[A version of this post appears on the O’Reilly Data blog.] One of the most popular offerings at Strata Santa Clara was Hardcore Data Science day. Over the next few weeks we hope to profile some…
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Time-turner: Strata Santa Clara 2014, day 2
There are so many good talks happening at the same time that it’s impossible to not miss out on good sessions. But imagine I had a time-turner necklace and could actually “attend” 2 (maybe 3) sessions…
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Time-turner: Strata Santa Clara 2014, day 1
There are so many good talks happening at the same time that it’s impossible to not miss out on good sessions. But imagine I had a time-turner necklace and could actually “attend” 2 (maybe 3) sessions…
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Graphs, Time-series, Dataviz, and Crowdsourcing at Strata Santa Clara 2014
There are many fantastic talks at Strata and it can be overwhelming to navigate the schedule. I plan to list talks I’m hoping to catch in a series of “time-turner” posts (check this blog on Wed/Thu…
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Business analysts want access to advanced analytics
[A version of this post appears on the O’Reilly Data blog and Forbes.] I talk with many new companies who build tools for business analysts and other non-technical users. These new tools streamline and simplify important…
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What I use for data visualization
[A version of this post appears on the O’Reilly Data blog.] Depending on the nature of the problem, data size, and deliverable, I still draw upon an array of tools for data visualization. As I survey…
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IPython: A unified environment for interactive data analysis
[A version of this post appears on the O’Reilly data blog and Forbes.] As I noted in a recent post on reproducing data projects, notebooks have become popular tools for maintaining, sharing, and replicating long data…
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A compelling family of DSLs for Data Science
[A version of this post appears on the O’Reilly Data blog.] An important reason why pydata tools and Spark appeal to data scientists is that they both cover many data science tasks and workloads (Spark users…
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Six reasons why I recommend scikit-learn
[A version of this post appears on the O’Reilly Data blog.] I use a variety of tools for advanced analytics, most recently I’ve been using Spark (and MLlib), R, scikit-learn, and GraphLab. When I need to…