My copy of Programming Collective Intelligence: Building Smart Web 2.0 Applications arrived in the mail today. I am fairly confident (more so after reading that Cosma Shalizi et al have recently received a grant from INET to apply these techniques to validate macroeconomic forecasting models) that the programming techniques taught in this book will be useful to me as a macroeconomist.
I am particularly interested in the techniques borrowed from statistical and machine learning theory (support-vector machines, genetic algorithms, genetic programming, etc).
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I'm afraid I don't know that book. Let me however point you to what is one of the most widely used standard references on machine learning and modern statistics, and deservedly so: The Elements of Statistical Learning. There's a free PDF of the whole book there.
ReplyDeleteMany thanks for the link! I will definitely put it on my reading list. The Collective Intelligence book I am working through seems very entry-level, but it does provided Python code and examples/exercises to work through...I find that when I am forced to program something (an algorithm) I learn it much faster/better.
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