<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Data-Science on Setu's (micro)blog</title><link>https://micro.setu.me/tags/data-science/</link><description>Recent content in Data-Science on Setu's (micro)blog</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 01 Jul 2019 23:01:17 -0700</lastBuildDate><atom:link href="https://micro.setu.me/tags/data-science/index.xml" rel="self" type="application/rss+xml"/><item><title>Data + Science</title><link>https://micro.setu.me/posts/data-science/</link><pubDate>Mon, 01 Jul 2019 23:01:17 -0700</pubDate><guid>https://micro.setu.me/posts/data-science/</guid><description>&lt;p>‘Data never lies; people do.’&lt;/p>
&lt;p>Data is an amusing artefact. It exists all around us, in many forms, and unless we know exactly how to read it, we are oblivious to it. It is no wonder that most professions are based in the ability to understand one specific type of data. We spend a quarter of our lives just learning about different types of data and figuring out which one we want to spend the rest of our lives around! What are skills if not the art of interpreting data? It is in this interpretation that lies are born from. Data doesn’t write stories, interpreters do. What comes from understanding the data is the hypotheses, observations, conclusions, drawn from the data. That is not what the data tells us; that is what the interpreter understands from the data, given their abilties.&lt;/p></description></item></channel></rss>