Today I’m going to write about MapReduce. It’s quite popular topic these days, and it’s the one I’m particularly interested in.

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Today I’ve found that Richard Szeliski, famous researcher from MSR, one of the major developers of the photosynth, is currently writing a computer vision book. It’s based on his CV course at Stanford and University of Washington. And here goes one very good thing: he had made drafts of his book available on his web page. Book already contains tons of useful information and it’s constantly growing and improving. Read it, mail Richard if you found some errors and keep looking for new drafts!

I've finally received "The Elements of Statistical Learning" book from Amazon. It's really great because it covers probably all the important machine learning topics including various regression and classification algorithms, model selection, graphical models, dimensionality reduction and many more. And this is also the first book covering boosting good (which is kind of important for me). Book authors, Trevor Hastie, Robert Tibshirani and Jerome Friedman are famous machine learning scientists from Stanford University. And the last one: book is published by Springer on an awesome paper with color plots. Holy crap, I like it!

Btw about Springer. Today I've found that one of the university shells I have access to is in the same university subnet where all the papers from SpringerLink are available for free. So I've written a little script that downloads requested article to my computer through that shell. Together with ACM account I've recently bought it gaves me acceess to almost every article I want.