Machine Learning An Algorithmic Perspective

ch2.py

# Code from Chapter 2 of Machine Learning: An Algorithmic Perspective (2nd Edition)

# by Stephen Marsland (http://stephenmonika.net)

# You are free to use, change, or redistribute the code in any way you wish for

# non-commercial purposes, but please maintain the name of the original author.

# This code comes with no warranty of any kind.

# Stephen Marsland, 2008, 2014

# Plots a 1D Gaussian function

from matplotlib import pylab

import pylab as pl

import numpy as np

gaussian = lambda x: 1/(np.sqrt(2*np.pi)*1.5)*np.exp(-(x-0)**2/(2*(1.5**2)))

x = np.arange(-5,5,0.01)

y = gaussian(x)

pl.ion()

pl.plot(x,y,'k',linewidth=3)

pl.xlabel('x')

pl.ylabel('y(x)')

pl.axis([-5,5,0,0.3])

pl.title('Gaussian Function (mean 0, standard deviation 1.5)')

pl.show()

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(base) C:\Users\USERNAME\Desktop>conda activate VIRTUALENV_NAME

(VIRTUALENV_NAME) C:\Users\USERNAME\Desktop>python ch1.py

(VIRTUALENV_NAME) C:\Users\USERNAME\Desktop>python -i ch1.py

- Run cmd

> python -i ch2.py

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