Machine Learning

这一阵为了工作上的关系，花了点时间学习了一下LDA算法，说实话，对于我这个学CS而非学数学的人来说，除了集体智慧编程这本书之外基本没怎么看过机器学习的人来说，一开始还真是摸不太到门道，前前后后快要四个月了，算是基本了解了这个算法的实现，记录一下，也供后来人快速入门做个参考。

一开始直接就下了Blei的原始的那篇论文来看，但是看了个开头就被Dirichlet分布和几个数学公式打倒，然后因为专心在写项目中的具体的代码，也就先放下了。但是因为发现完全忘记了本科学的概率和统计的内容，只好回头去看大学时候概率论的教材，发现早不知道借给谁了，于是上网买了…

I haven’t posted in awhile, but it’s not because I’m lazy (well, not ONLY because I’m lazy). I’ve put working on barbot on hold while I take Stanford’s artificial intelligence (www.ai-class.com) and machine learning (www.ml-class.org) classes.
 
 If you haven’t heard about the classes (the…

On Tuesday March 22nd @injust and @rathboma gave a talk at the NYC Machine Learning Meetup (a big thanks to Paul Dix for inviting us).

So I didn’t post an update about the AAAI 2011 conference every day, but really, this is more posts than I would have predicted with my prior model of my behaviour so it’s pretty good. I also wrote a separate post talking about the Computational Sustainability track.

This is just a few quick few…

In earlier blog posts I talked about Semantic Proximity of concepts and using Linked Data to derive a notion of semantic…