I don't get it. DST installs 3 tools: R, Python, and DST itself. R and its packages are VERY easy to install, Python and its packages are pretty easy to install, and you don't need DST until you choose to install DST. It's not like they are putting a large hard to configure stack (like Hadoop/Mahout/Pig/Hive/Spark ...) for you.
I half-expected a "toolbox" more like Orange.<p>(<a href="http://orange.biolab.si/" rel="nofollow">http://orange.biolab.si/</a>)
Would love to see a few basic libraries install ahead of time (NumPy and SciPy, namely) and hear about performance implications of running virtually.<p>Cool tool though - I've done data science work for a few companies now and the most frustrating thing is always getting set up on their stack.
Appears to be unrelated from the Data Science Toolkit virtual machine image which frontpaged yesterday<p><a href="https://news.ycombinator.com/item?id=7835097" rel="nofollow">https://news.ycombinator.com/item?id=7835097</a>
I appreciate author's effort. But for any aspiring data scientists this website is much much more useful:<p><a href="http://www.datasciencetoolkit.org/" rel="nofollow">http://www.datasciencetoolkit.org/</a>
Looks cool. When it reaches 1.0 you might want to include Beaker: <a href="http://BeakerNotebook.com" rel="nofollow">http://BeakerNotebook.com</a>