<story><title>Mining of Massive Datasets</title><url>http://mmds.org/</url></story><parent_chain></parent_chain><comment><author>amitkgupta84</author><text>I&amp;#x27;m taking this course right now, I&amp;#x27;m a little ambivalent about it.  They cover various machine learning algorithms, which one can learn anywhere, but they also talk about how to deal with these things in a massive data context.  The pragmatic tools needed to wrangle large amounts of data so that you can apply your usual ML algorithms to it is very nice to see.&lt;p&gt;That said, I don&amp;#x27;t feel like I&amp;#x27;m learning concepts.  So far, the techniques have felt like: break up the data into chunks this way, apply a bunch of hash functions that way, this is what ended up working for this particular problem.  I guess if you work in the field, the tools you&amp;#x27;re exposed to will inspire things in your own work, and you&amp;#x27;ll feel more like you&amp;#x27;re building a general framework.&lt;p&gt;The homeworks are terrible.  There are no mandatory programming assignments, and the one optional one does nothing to gradually work up to applying the stuff they teach you, it&amp;#x27;s just, here&amp;#x27;s a massive zip that won&amp;#x27;t fit on your hard drive, here&amp;#x27;s an uninteresting computational question to answer about it, go for it.&lt;p&gt;The remaining (basic) homeworks are quizzes and they&amp;#x27;re incredibly tedious.  (There are advanced homeworks as well, but it hasn&amp;#x27;t been that inspiring).  One of the recent homeworks was really just a rehash of some high school linear algebra, another one involved doing some computations with a bunch of different points.  The points weren&amp;#x27;t provided in a list, they were drawn onto a jpeg so you had to manually copy all of them down.  That&amp;#x27;s the kind of course it&amp;#x27;s been.&lt;p&gt;It&amp;#x27;s a very light weight course, which is nice if you&amp;#x27;re working.  If your basic math skills are good and you already have some familiarity with ML and distributed computing, 5 hrs&amp;#x2F;wk is enough to watch the videos (at 2x speed plus occasionally hitting the 10-second-fast-forward) and do the basic homeworks.</text></comment>
<story><title>Mining of Massive Datasets</title><url>http://mmds.org/</url></story><parent_chain></parent_chain><comment><author>koffiekop</author><text>We are currently using this book for a course at the Leiden institute for advanced computer science. It&amp;#x27;s pretty up to date.&lt;p&gt;It covers LSH, cosine similarity, Jaccard similarity as well as recommender systems applicable to the Netflix challenge and so forth.</text></comment>