Steve discusses the need for expansion of college statistics curricula into data and computation for the analytics business world.
In this article, we review some of the challenges with using standard statistical techniques with big data analysis, and introduces a practical and robust process for resampling-based analysis of big data.
Even with all the support sites that provide support in flexibly-queryable online documentation there is still a need for cheat sheets. The latest cheat sheets for R data.table package and Python Basics for Python are still extremely applicable.
Like the scripting languages tradition of Perl and Python, Ruby's ideal for many core munging challenges of data science. The combination of Ruby data types with methods, blocks and iterators, makes for very powerful code. But does the rest of Ruby fit the bill?
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