# 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 | ||

+ | *Python Linear Least Squares Fitting Routine: http://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.lstsq.html |

## Revision as of 11:32, 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

- Some good books on linear regression:
- Excellent ebook: http://www-stat.stanford.edu/~tibs/ElemStatLearn/
- 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

- Python Linear Least Squares Fitting Routine: http://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.lstsq.html