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	<title>Ivan Idris Blog</title>
	
	<link>http://ivanidris.net/wordpress</link>
	<description>Author of NumPy Beginner's Guide &amp; NumPy Cookbook</description>
	<lastBuildDate>Thu, 23 May 2013 15:01:08 +0000</lastBuildDate>
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		<title>Moving Average Temperature Model with Lag 1</title>
		<link>http://feedproxy.google.com/~r/IvanIdrisBlog/~3/SrxhAMROE4E/moving-average-temperature-model-with-lag-1</link>
		<comments>http://ivanidris.net/wordpress/index.php/2013/05/23/moving-average-temperature-model-with-lag-1#comments</comments>
		<pubDate>Thu, 23 May 2013 15:01:08 +0000</pubDate>
		<dc:creator>Ivan Idris</dc:creator>
				<category><![CDATA[programming]]></category>
		<category><![CDATA[numpy]]></category>
		<category><![CDATA[python]]></category>

		<guid isPermaLink="false">http://ivanidris.net/wordpress/?p=1337</guid>
		<description>This entry is part 20 of 20 in the series NumPy WeatherThe moving average model of a time-series represents the data as oscillations around the mean of the data. It is assumed that the lag components are white noise (not &amp;#8230; &lt;a href="http://ivanidris.net/wordpress/index.php/2013/05/23/moving-average-temperature-model-with-lag-1"&gt;Continue reading &lt;span class="meta-nav"&gt;&amp;#8594;&lt;/span&gt;&lt;/a&gt;&lt;img src="http://feeds.feedburner.com/~r/IvanIdrisBlog/~4/SrxhAMROE4E" height="1" width="1"/&gt;</description>
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		<series:name><![CDATA[NumPy Weather]]></series:name>
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		<item>
		<title>Coursera Machine Learning Week 5</title>
		<link>http://feedproxy.google.com/~r/IvanIdrisBlog/~3/UQN3OAgiNTI/coursera-machine-learning-week-5</link>
		<comments>http://ivanidris.net/wordpress/index.php/2013/05/22/coursera-machine-learning-week-5#comments</comments>
		<pubDate>Wed, 22 May 2013 16:37:46 +0000</pubDate>
		<dc:creator>Ivan Idris</dc:creator>
				<category><![CDATA[Uncategorized]]></category>

		<guid isPermaLink="false">http://ivanidris.net/wordpress/?p=1331</guid>
		<description>This week&amp;#8217;s lecture is again about Neural Networks. As a aside, my Firefox settings seem to not work that well with the Coursera user interface. So I switched to Safari. Now the &amp;#8220;speed up&amp;#8221; buttons work for me. I accelerated &amp;#8230; &lt;a href="http://ivanidris.net/wordpress/index.php/2013/05/22/coursera-machine-learning-week-5"&gt;Continue reading &lt;span class="meta-nav"&gt;&amp;#8594;&lt;/span&gt;&lt;/a&gt;&lt;img src="http://feeds.feedburner.com/~r/IvanIdrisBlog/~4/UQN3OAgiNTI" height="1" width="1"/&gt;</description>
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		<item>
		<title>Review of “Cryptonomicon”</title>
		<link>http://feedproxy.google.com/~r/IvanIdrisBlog/~3/pfi207mbtJY/review-of-cryptonomicon</link>
		<comments>http://ivanidris.net/wordpress/index.php/2013/05/21/review-of-cryptonomicon#comments</comments>
		<pubDate>Tue, 21 May 2013 16:08:48 +0000</pubDate>
		<dc:creator>Ivan Idris</dc:creator>
				<category><![CDATA[books]]></category>

		<guid isPermaLink="false">http://ivanidris.net/wordpress/?p=1320</guid>
		<description>&amp;#8220;Cryptonomicon&amp;#8221; by Neal Stephenson was written before the Baroque Cycle trilogy and is closely related to it. However, the events in this book occur after the Baroque Cycle. A lot of the action in &amp;#8220;Cryptonomicon&amp;#8221; takes place in World War &amp;#8230; &lt;a href="http://ivanidris.net/wordpress/index.php/2013/05/21/review-of-cryptonomicon"&gt;Continue reading &lt;span class="meta-nav"&gt;&amp;#8594;&lt;/span&gt;&lt;/a&gt;&lt;img src="http://feeds.feedburner.com/~r/IvanIdrisBlog/~4/pfi207mbtJY" height="1" width="1"/&gt;</description>
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		<item>
		<title>Day of Year Temperature Fit Take 2</title>
		<link>http://feedproxy.google.com/~r/IvanIdrisBlog/~3/6c7sAIoTuN0/day-of-year-temperature-fit-take-2</link>
		<comments>http://ivanidris.net/wordpress/index.php/2013/05/20/day-of-year-temperature-fit-take-2#comments</comments>
		<pubDate>Mon, 20 May 2013 16:18:15 +0000</pubDate>
		<dc:creator>Ivan Idris</dc:creator>
				<category><![CDATA[programming]]></category>
		<category><![CDATA[numpy]]></category>
		<category><![CDATA[python]]></category>

		<guid isPermaLink="false">http://ivanidris.net/wordpress/?p=1312</guid>
		<description>This entry is part 19 of 20 in the series NumPy WeatherYeah, turns out some people didn&amp;#8217;t like the quadratic polynomial approximation for the day of the year temperature fit. So let&amp;#8217;s try a trigonometric function and fit again using &amp;#8230; &lt;a href="http://ivanidris.net/wordpress/index.php/2013/05/20/day-of-year-temperature-fit-take-2"&gt;Continue reading &lt;span class="meta-nav"&gt;&amp;#8594;&lt;/span&gt;&lt;/a&gt;&lt;img src="http://feeds.feedburner.com/~r/IvanIdrisBlog/~4/6c7sAIoTuN0" height="1" width="1"/&gt;</description>
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		<slash:comments>0</slash:comments>
	
		<series:name><![CDATA[NumPy Weather]]></series:name>
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		<item>
		<title>Modeling Temperature with the SciPy leastsq function</title>
		<link>http://feedproxy.google.com/~r/IvanIdrisBlog/~3/DStYIgePiBM/modeling-temperature-with-the-scipy-leastsq-function</link>
		<comments>http://ivanidris.net/wordpress/index.php/2013/05/19/modeling-temperature-with-the-scipy-leastsq-function#comments</comments>
		<pubDate>Sun, 19 May 2013 15:48:12 +0000</pubDate>
		<dc:creator>Ivan Idris</dc:creator>
				<category><![CDATA[programming]]></category>
		<category><![CDATA[numpy]]></category>
		<category><![CDATA[python]]></category>

		<guid isPermaLink="false">http://ivanidris.net/wordpress/?p=1305</guid>
		<description>This entry is part 18 of 20 in the series NumPy WeatherSo now we have two ideas. Either the temperature today depends on the temperature yesterday and the day before yesterday. And we assume that some kind of linear combination &amp;#8230; &lt;a href="http://ivanidris.net/wordpress/index.php/2013/05/19/modeling-temperature-with-the-scipy-leastsq-function"&gt;Continue reading &lt;span class="meta-nav"&gt;&amp;#8594;&lt;/span&gt;&lt;/a&gt;&lt;img src="http://feeds.feedburner.com/~r/IvanIdrisBlog/~4/DStYIgePiBM" height="1" width="1"/&gt;</description>
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		<series:name><![CDATA[NumPy Weather]]></series:name>
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		<item>
		<title>Weekly Standup IV</title>
		<link>http://feedproxy.google.com/~r/IvanIdrisBlog/~3/GD_s8X1XoGo/weekly-standup-iv</link>
		<comments>http://ivanidris.net/wordpress/index.php/2013/05/18/weekly-standup-iv#comments</comments>
		<pubDate>Sat, 18 May 2013 15:51:42 +0000</pubDate>
		<dc:creator>Ivan Idris</dc:creator>
				<category><![CDATA[Uncategorized]]></category>

		<guid isPermaLink="false">http://ivanidris.net/wordpress/?p=1297</guid>
		<description>First a joke. Question: why did the Scrum chicken cross the road? Answer: it was committed to Sprint! Another old classic. What did I do? This week. Added to the NumPy Weather spike &amp;#8211; Day of the Year Temperature Model, &amp;#8230; &lt;a href="http://ivanidris.net/wordpress/index.php/2013/05/18/weekly-standup-iv"&gt;Continue reading &lt;span class="meta-nav"&gt;&amp;#8594;&lt;/span&gt;&lt;/a&gt;&lt;img src="http://feeds.feedburner.com/~r/IvanIdrisBlog/~4/GD_s8X1XoGo" height="1" width="1"/&gt;</description>
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		<item>
		<title>Day of the Year Temperature Model</title>
		<link>http://feedproxy.google.com/~r/IvanIdrisBlog/~3/UBY0xt9wPoI/day-of-the-year-temperature-model</link>
		<comments>http://ivanidris.net/wordpress/index.php/2013/05/17/day-of-the-year-temperature-model#comments</comments>
		<pubDate>Fri, 17 May 2013 10:41:26 +0000</pubDate>
		<dc:creator>Ivan Idris</dc:creator>
				<category><![CDATA[programming]]></category>
		<category><![CDATA[numpy]]></category>
		<category><![CDATA[python]]></category>

		<guid isPermaLink="false">http://ivanidris.net/wordpress/?p=1286</guid>
		<description>This entry is part 17 of 20 in the series NumPy WeatherContinuing with the amazing work we did yesterday, I would like to propose a new model, where temperature is a function of the day of the year (between 1 &amp;#8230; &lt;a href="http://ivanidris.net/wordpress/index.php/2013/05/17/day-of-the-year-temperature-model"&gt;Continue reading &lt;span class="meta-nav"&gt;&amp;#8594;&lt;/span&gt;&lt;/a&gt;&lt;img src="http://feeds.feedburner.com/~r/IvanIdrisBlog/~4/UBY0xt9wPoI" height="1" width="1"/&gt;</description>
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		<series:name><![CDATA[NumPy Weather]]></series:name>
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		<item>
		<title>Intrayear Daily Average Temperatures</title>
		<link>http://feedproxy.google.com/~r/IvanIdrisBlog/~3/yFqDHYFXzDc/intrayear-daily-average-temperatures</link>
		<comments>http://ivanidris.net/wordpress/index.php/2013/05/16/intrayear-daily-average-temperatures#comments</comments>
		<pubDate>Thu, 16 May 2013 19:09:02 +0000</pubDate>
		<dc:creator>Ivan Idris</dc:creator>
				<category><![CDATA[programming]]></category>
		<category><![CDATA[numpy]]></category>
		<category><![CDATA[python]]></category>

		<guid isPermaLink="false">http://ivanidris.net/wordpress/?p=1276</guid>
		<description>This entry is part 16 of 20 in the series NumPy WeatherApologies for the title, but I couldn&amp;#8217;t come up with anything better. We are going to have a look at the temperature variation within an year by converting dates &amp;#8230; &lt;a href="http://ivanidris.net/wordpress/index.php/2013/05/16/intrayear-daily-average-temperatures"&gt;Continue reading &lt;span class="meta-nav"&gt;&amp;#8594;&lt;/span&gt;&lt;/a&gt;&lt;img src="http://feeds.feedburner.com/~r/IvanIdrisBlog/~4/yFqDHYFXzDc" height="1" width="1"/&gt;</description>
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		<series:name><![CDATA[NumPy Weather]]></series:name>
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		<item>
		<title>Coursera Machine Learning Week 4</title>
		<link>http://feedproxy.google.com/~r/IvanIdrisBlog/~3/26rOlYFITnY/coursera-machine-learning-week-4</link>
		<comments>http://ivanidris.net/wordpress/index.php/2013/05/15/coursera-machine-learning-week-4#comments</comments>
		<pubDate>Wed, 15 May 2013 14:51:16 +0000</pubDate>
		<dc:creator>Ivan Idris</dc:creator>
				<category><![CDATA[Uncategorized]]></category>

		<guid isPermaLink="false">http://ivanidris.net/wordpress/?p=1270</guid>
		<description>I was a bit distracted when listening to the video lectures of Coursera Machine Learning week 4. Fortunately it was a short session, so hopefully I didn&amp;#8217;t miss much. This week&amp;#8217;s lectures were about neural networks. Neural networks are networks &amp;#8230; &lt;a href="http://ivanidris.net/wordpress/index.php/2013/05/15/coursera-machine-learning-week-4"&gt;Continue reading &lt;span class="meta-nav"&gt;&amp;#8594;&lt;/span&gt;&lt;/a&gt;&lt;img src="http://feeds.feedburner.com/~r/IvanIdrisBlog/~4/26rOlYFITnY" height="1" width="1"/&gt;</description>
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		<item>
		<title>Review of “Anathem”</title>
		<link>http://feedproxy.google.com/~r/IvanIdrisBlog/~3/TP6gbF6SFuk/review-of-anathem</link>
		<comments>http://ivanidris.net/wordpress/index.php/2013/05/14/review-of-anathem#comments</comments>
		<pubDate>Tue, 14 May 2013 15:40:26 +0000</pubDate>
		<dc:creator>Ivan Idris</dc:creator>
				<category><![CDATA[books]]></category>

		<guid isPermaLink="false">http://ivanidris.net/wordpress/?p=1264</guid>
		<description>&amp;#8220;Anathem&amp;#8221; is another science fiction book by Neal Stephenson. I would say that it is hard science fiction, since it is about parallel universes (multiverse), quantum mechanics, mathematics and philosophy. The author tries to teach his readers a bit along &amp;#8230; &lt;a href="http://ivanidris.net/wordpress/index.php/2013/05/14/review-of-anathem"&gt;Continue reading &lt;span class="meta-nav"&gt;&amp;#8594;&lt;/span&gt;&lt;/a&gt;&lt;img src="http://feeds.feedburner.com/~r/IvanIdrisBlog/~4/TP6gbF6SFuk" height="1" width="1"/&gt;</description>
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