Originally submitted at O’Reilly
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Hilary Mason: Advanced Machine Learning
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<a href="http://shop.oreilly.com/product/0636920025610.do" style="display: none;" class="url fn"><span class="fn">Hilary Mason: Advanced Machine Learning</span></a></div>
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<strong class="summary">More “Intro to Machine Learning part 2”</strong>
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By <strong>Jim Schubert</strong> from <strong>Richmond, VA</strong> on <strong><abbr title="2012922T1200-0800" class="dtreviewed" style="border: none; text-decoration: none;">9/22/2012</abbr></strong>
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<span class="rating">4</span>out of 5
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<strong>Pros: </strong>Helpful examples, Easy to understand
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<strong>Cons: </strong>Too basic, Not comprehensive enough
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<strong>Best Uses: </strong>Novice, Student
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<strong>Describe Yourself: </strong>Developer
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I watched this video as part of O’Reilly Media’s blogger program. I haven’t worked with machine learning topics in the past, and I was interested to learn a bit from this video. It turns out that I use many of the machine learning concepts in the linux terminal almost daily, but on much smaller data (personal computer logs). I’ve even parsed Apache logs in almost the same way as presented in this video’s “Learning from your data” segment.<br xmlns:pr="xalan://com.pufferfish.core.beans.xmlbuilders.xsl.Functions" /><br />At first, I was little confused why this video is called “Advanced Machine Learning” because I didn’t feel like any of the topics were all too advanced. Each segment seems to only skim the surface of a very general topic. In fact, it seems to me that this video is more of a continuation of Ms. Mason’s other Machine Learning video on O’Reilly– “An Introduction to Machine Learning with Web Data.” It may be more appropriately named “An introduction to data analysis”, and that’s not a bad thing! Don’t be turned away by a misleading title. Fair warning: I’ve rated the video based on the content with my proposed title.
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If you’re looking for an in-depth discussion of machine learning algorithms, this isn’t the video for you. If you’re looking for an introduction in getting things done with data, you should check out this video. Although the amount of information is pretty light, it is still a good way to get your start conceptually. If you look at the scripts and sample data provided in the code repository, you’ll be off to a good start to learn more about your data.
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For instance, Hillary makes it a point to break things down into a few simple steps:
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1) What is your data?<br />2) What do you want to learn from your data?<br />3) How to extract that information.
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Again, I wouldn’t recommend this video if you’re software engineer with a desire to learn in-depth machine learning algorithms. I do recommend this video if you’re interested in understanding some fundamentals of machine learning and how they’re applied in some advanced production scenarios (especially at bit.ly).
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I also recommend checking out the code examples and learning the basics of the python modules used in the scripts. They will help you analyze your data in a meaningful way.
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