<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>pictures on DataScience.LA</title><link>https://datasciencela.github.io/tag/pictures/</link><description>Recent content in pictures on DataScience.LA</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><copyright>DataScience.LA, 2014–2021 · Read-only archive: comments are closed.</copyright><lastBuildDate>Thu, 08 Jan 2015 21:09:54 -0800</lastBuildDate><atom:link href="https://datasciencela.github.io/tag/pictures/index.xml" rel="self" type="application/rss+xml"/><item><title>Data Science LA Meetup Summary: Data Science @ IRIS.TV</title><link>https://datasciencela.github.io/data-science-la-meetup-summary-data-science-iris-tv/</link><pubDate>Thu, 08 Jan 2015 20:00:26 -0800</pubDate><guid>https://datasciencela.github.io/data-science-la-meetup-summary-data-science-iris-tv/</guid><description>&lt;p&gt;&lt;em&gt;(Posting the slides and video recording from this event is long overdue - our apologies for the delay.)&lt;/em&gt;&lt;/p&gt;&#10;&lt;p&gt;At the September LA Data Science/Machine Learning meetup we had &lt;a href="http://iris.tv/"&gt;IRIS.TV&lt;/a&gt;&amp;rsquo;s Chief Data Scientist &lt;a href="https://www.linkedin.com/pub/thomas-j-sullivan-ph-d/27/744/39a"&gt;Tom Sullivan&lt;/a&gt; and VP of Engineering &lt;a href="https://www.linkedin.com/pub/joel-spitalnik/55/220/978"&gt;Joel Spitalnik&lt;/a&gt; presenting.&lt;/p&gt;&#10;&lt;p&gt;IRIS.TV is a video recommendation engine, and in their excellent talk Tom &amp;amp; Joel shared with us their approach to personalization and how they use machine learning to achieve their goals. They also shared the architecture of their systems, including how data is flowing between the various parts (i.e. the ETL pipeline). One thing that popped up as a question and I found interesting is that the usage of R and Python in their company is split 50-50. In fact, while Tom is using mainly R, Joel is using mainly Python. While this is perhaps unusual at a relatively small startup, our &lt;a href="https://datasciencela.github.io/data-science-toolbox-survey-results-surprise-r-and-python-win/"&gt;survey on software tools used for data science&lt;/a&gt; revealed that most data scientists in LA (at least those attending the meetups) are using R or Python, with a roughly equal split/small advantage for R. It just happens that for obvious reasons (such as network effects) that one tool dominates in most companies.&lt;/p&gt;</description></item></channel></rss>