mriley
Swiftype (YC W12) is hiring a DevOps Engineer
Most websites have terrible site search. Founded by the engineers who built Scribd’s search, Swiftype (http://swiftype.com) is fixing that by offering a dead-simple modern search for sites ranging from your sister’s Tumblr to Alexa Top 100 behemoths. We are a hosted service that powers a key feature on tens of thousands of websites, and as such, we place tremendous importance on the reliability...
Swiftype launches WordPress Plugin and improved Tumblr support
Swiftype (YC W12) is hiring DevOps
Most websites have terrible site search. Founded by the engineers who built Scribd’s search, Swiftype (http://swiftype.com) is fixing that by offering a dead-simple modern search for sites ranging from your sister’s Tumblr to Alexa Top 100 behemoths. We are a hosted service that powers a key feature on thousands of websites, and as such, we place tremendous importance on the reliability and...
Swiftype (YC W12) is hiring full-stack engineers to build better search software
Swiftype is building search software for the next generation of websites and applications, and we're looking for great engineers to help us build out our infrastructure and product line. We're a small team of highly technical, product-focused engineers with extensive search experience. As a small team, we're looking for early engineers who are self-motivated, resourceful, and enjoy the...
HomeAway - Rental Reviews and NLP: Clustering
The Story Behind That 9,000-Word Quora Post on Airplane Cockpits
Tenured Prof Departs Stanford, Hoping to Teach 500k Students at Startup
TheLikestream, Digg For Facebook “Likes”
Introduction to Tries
I can see this idea applied to drink recipes, though. I often have 3 or 4 half-empty bottles of different types of liquor- it would be great to get a list of 10 different drinks I could make with friends. On second thought, $10 says there's already a Facebook App that does exactly that...
If you're interested in introductory data mining stuff, I would recommend Tan's Introduction to Data Mining: http://www-users.cs.umn.edu/~kumar/dmbook/index.php
I would also suggest Elements of Statistical Learning: http://www-stat.stanford.edu/~tibs/ElemStatLearn/
As well as Duda, Hart, and Stork's Pattern Classification: http://rii.ricoh.com/~stork/DHS.html