Python code for "Machine learning: a probabilistic perspective"
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Latest commit fb939b9 Oct 28, 2018

README.md

pyprobml

Python 3 code for "Machine learning: a probabilistic perspective" (http://people.cs.ubc.ca/~murphyk/MLbook/) v2.0.

You should run the code from the repo root ('pyprobml' directory) using module execution, e.g.,

python -m examples.LMSdemo

To run all the examples you can use

ls examples/.py | sed 's///./' | sed s/.[^.]$// | xargs -n 1 python -m

from the repo root. This lists all the Python files under examples, turns the slash into a period, then removes the .py extension and finally feeds each line into python -m.