<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>monk_the_dog</author><text>If you already have a little exposure to machine learing, let me recomend an interesting review paper [1] on random forests: &lt;a href=&quot;http://research.microsoft.com/pubs/155552/decisionForests_MSR_TR_2011_114.pdf&quot; rel=&quot;nofollow&quot;&gt;http://research.microsoft.com/pubs/155552/decisionForests_MS...&lt;/a&gt;&lt;p&gt;It isn&apos;t everything you need know in 30 minutes, but it&apos;s a concrete coverage of lots of topics in machine learning in under 150 pages. Here&apos;s why I&apos;m recomending this paper:&lt;p&gt;* The algoritm is easy to understand.&lt;p&gt;* It can handle classification, regression, semi-supervised learning, manifold learning, and density estimation. The paper gives an introduction to each of these topics as well as a unified framework to implement each algorithm.&lt;p&gt;* It can handle categorical data and missing data [2]&lt;p&gt;* It gives as good results as other state of the art algorithms.&lt;p&gt;* The paper is well-written and easy to understand for someone without a deep background in machine learning.&lt;p&gt;[1] It&apos;s mostly a review paper. Using random forests for density estimation is new.&lt;p&gt;[2] This review paper doesn&apos;t cover categorical data or missing data.</text><parent_chain></parent_chain></comment><story><title>Everything you need to know about Machine Learning in 30 minutes or less</title><url>http://www.hilarymason.com/presentations-2/devs-love-bacon-everything-you-need-to-know-about-machine-learning-in-30-minutes-or-less/?utm_source=twitterfeed&amp;utm_medium=twitter</url><text></text></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>marcelsalathe</author><text>Nice talk. The example of google translate is not a good one though. Say you translate from language A to language B with 99% accuracy, and  vice versa, which would be pretty awesome, you&apos;d still have a substantial quality decay after only a few back and forth translations (0.99^x where x is the number of translation steps).</text><parent_chain></parent_chain></comment><story><title>Everything you need to know about Machine Learning in 30 minutes or less</title><url>http://www.hilarymason.com/presentations-2/devs-love-bacon-everything-you-need-to-know-about-machine-learning-in-30-minutes-or-less/?utm_source=twitterfeed&amp;utm_medium=twitter</url><text></text></story>