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    <title>Data Science on Nyghtowl</title>
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      <title>Graphlab &amp; ODBC</title>
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      <pubDate>Sun, 25 Jan 2015 22:33:27 +0000</pubDate>
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      <description>&lt;p&gt;For those out there working with Dato(Graphlab) and trying to setup an ODBC connection to just pull all the data straight into the SFrame, here are some tips I’ve learned from troubleshooting.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;What is ODBC?&lt;/strong&gt;&lt;br&gt;&#xA;Open Database Connectivity which is a middleware API to help standardize and simplify access to database management systems.&lt;/p&gt;&#xA;&lt;p&gt;**Connection Pointers:**There are a number of links on odbc setup but it was a little tricky to get it to work with Graphlab, Linux and OSX and Graphlab’s documentation is a little sparse in that area right now.&lt;/p&gt;</description>
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      <title>2014 Summer == Full Time Data Science Work</title>
      <link>https://nyghtowl.com/posts/2014/08/2014-summer-full-time-data-science-work/</link>
      <pubDate>Sun, 31 Aug 2014 12:30:00 +0000</pubDate>
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      <description>&lt;p&gt;For the last three months I have been working at Change.org as a data scientist and engineer. Its been a great experience so far and I’m blown away that this is where I landed after starting this journey a year plus ago.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Impostor Syndrome&lt;/strong&gt;&lt;br&gt;&#xA;I’ve coached others going through moving into engineering about how to believe in themselves and they are smarter than they think. I totally get that you want to fake the confidence till you get there. Don’t be cocky just be resolved to figure stuff out.&lt;/p&gt;</description>
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      <title>Zipfian First Week Rundown</title>
      <link>https://nyghtowl.com/posts/2014/01/zipfian-first-week-rundown/</link>
      <pubDate>Sun, 26 Jan 2014 09:32:49 +0000</pubDate>
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      <description>&lt;p&gt;First week of Zipfian is already done and it does remind me how during Hackbright it felt like it went so fast. The focus for the week was about exposing us to core tools we will use as well as the main activities/processes around working with data.&lt;/p&gt;&#xA;&lt;p&gt;&lt;strong&gt;Week Summary&lt;/strong&gt;&lt;/p&gt;&#xA;&lt;p&gt;The main tools used this week were Python, iPython, Git and Bash, and we went through three different exercises where we were gathering, cleaning, exploring and sometimes reporting data. A large part of our exercises throughout the program will be done in Python and we spent 4 of the 5 days using it. This is a bit of a shift for the school because they split more time with R in the last session, and it has to do with the growing popularity of using Python for data science. There’s a great article I read recently on the subject at &lt;a href=&#34;http://www.r-bloggers.com/the-homogenization-of-scientific-computing-or-why-python-is-steadily-eating-other-languages-lunch/&#34;&gt;R-bloggers&lt;/a&gt;. We will still use R but the emphasis is more Python.&lt;/p&gt;</description>
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      <title>Try: Data Science Except: Monty’s Bayes Example</title>
      <link>https://nyghtowl.com/posts/2014/01/try-data-science-except-montys-bayes-example/</link>
      <pubDate>Mon, 20 Jan 2014 21:45:19 +0000</pubDate>
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      <description>&lt;p&gt;Great first day at Zipfian. Definitely a different experience starting from Hackbright but some similarities. Granted there are the obvious differences of the content focus on data science vs. web application development as well as 20% women in the class vs. 100%. Plus I’m not the oldest or the youngest of the group. We have a really nice mix of people from various parts of the country and a myriad of backgrounds. Though there is a lot PhDs and/or engineering backgrounds. It was a much quieter energy to the start of the class even though you could tell there was some nervousness.&lt;/p&gt;</description>
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