<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Probability on Brave New Geek</title><link>https://bravenewgeek.com/tag/probability/</link><description>Recent content in Probability on Brave New Geek</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 13 Sep 2018 23:23:09 +0600</lastBuildDate><atom:link href="https://bravenewgeek.com/tag/probability/index.xml" rel="self" type="application/rss+xml"/><item><title>Probabilistic algorithms for fun and pseudorandom profit</title><link>https://bravenewgeek.com/probabilistic-algorithms-for-fun-and-pseudorandom-profit/</link><pubDate>Sun, 06 Dec 2015 13:00:19 -0600</pubDate><guid>https://bravenewgeek.com/probabilistic-algorithms-for-fun-and-pseudorandom-profit/</guid><description>&lt;iframe loading="lazy" style="border: 1px solid #CCC; border-width: 1px; margin-bottom: 5px; max-width: 100%;" src="//www.slideshare.net/slideshow/embed_code/key/u8dzHRRAHnnItb" width="595" height="485" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" allowfullscreen="allowfullscreen"&gt;&lt;/iframe&gt;
&lt;p&gt;&lt;strong&gt;&lt;a href="//www.slideshare.net/TylerTreat/probabilistic-algorithms-for-fun-and-pseudorandom-profit" title="Probabilistic algorithms for fun and pseudorandom profit"&gt;Probabilistic algorithms for fun and pseudorandom profit&lt;/a&gt;&lt;/strong&gt; from &lt;strong&gt;&lt;a href="//www.slideshare.net/TylerTreat"&gt;Tyler Treat&lt;/a&gt;&lt;/strong&gt;&lt;/p&gt;</description></item><item><title>Stream Processing and Probabilistic Methods: Data at Scale</title><link>https://bravenewgeek.com/stream-processing-and-probabilistic-methods/</link><pubDate>Fri, 13 Feb 2015 10:49:07 -0600</pubDate><guid>https://bravenewgeek.com/stream-processing-and-probabilistic-methods/</guid><description>&lt;p&gt;Stream processing and related abstractions have become all the rage following the rise of systems like Apache Kafka, Samza, and the &lt;a href="http://en.wikipedia.org/wiki/Lambda_architecture"&gt;Lambda architecture&lt;/a&gt;. Applying the idea of immutable, append-only &lt;a href="http://blog.confluent.io/2015/01/29/making-sense-of-stream-processing/"&gt;event sourcing&lt;/a&gt; means we’re storing more data than ever before. However, as the cost of storage continues to decline, it’s becoming more feasible to store more data for longer periods of time. With immutability, how the data &lt;em&gt;lives&lt;/em&gt; isn’t interesting anymore. It’s all about how it &lt;em&gt;moves&lt;/em&gt;.&lt;/p&gt;</description></item><item><title>Probabilistic Primality Testing</title><link>https://bravenewgeek.com/probabilistic-primality-testing/</link><pubDate>Sun, 02 Dec 2012 08:30:40 +0600</pubDate><guid>https://bravenewgeek.com/probabilistic-primality-testing/</guid><description>&lt;p&gt;An exceedingly common question asked in coding interviews is to write a function, method, algorithm, whatever to determine if a number is prime. Prime numbers have a wide range of applications in computer science, particularly with regard to cryptography. The idea is that factoring large numbers into their prime factors is extremely difficult.&lt;/p&gt;
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&lt;p&gt;“Because both the system’s privacy and the security of digital money depend on encryption, a breakthrough in mathematics or computer science that defeats the cryptographic system could be a disaster. The obvious mathematical breakthrough would be the development of an easy way to factor large prime numbers.” -Bill Gates, &lt;a href="http://www.amazon.com/Road-Ahead-Book-CD-Pack/dp/1405879327"&gt;The Road Ahead&lt;/a&gt;&lt;/p&gt;</description></item></channel></rss>