Machine Learning Meetup Notes: 2010-04-21

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**Classic ML Book: http://www.amazon.com/Pattern-Classification-2nd-Richard-Duda/dp/0471056693
 
**Classic ML Book: http://www.amazon.com/Pattern-Classification-2nd-Richard-Duda/dp/0471056693
 
**Another ML Book (passed around in meetup): http://www.amazon.com/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738
 
**Another ML Book (passed around in meetup): http://www.amazon.com/Pattern-Recognition-Learning-Information-Statistics/dp/0387310738
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*Writeups on Optimization
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**Gradient Descent/Conjugate Gradient: http://www.cs.cmu.edu/~quake-papers/painless-conjugate-gradient.pdf
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**Least Angle Regression: http://www-stat.stanford.edu/~hastie/Papers/LARS/LeastAngle_2002.pdf
 
*Python Linear Least Squares Fitting Routine: http://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.lstsq.html
 
*Python Linear Least Squares Fitting Routine: http://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.lstsq.html

Revision as of 11:34, 22 April 2010

Overview

  • Mike S talked about linear regression.
  • Overview of linear least squares
  • Talked about gradient descent
  • Passed around some python code for doing least squares

Details

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