"Python" Machinelearning Machine Learning Introduction _ Efficiency Comparison

Efficiency comparison:

It's a cliché, but this time with a new module,

Run Time Test Module Timeti:

1 ImportTimeit2 3normal = Timeit.timeit ('sum (x*x for x in range )', number=10000)4NATIVE_NP = Timeit.timeit ('sum (na*na)',#Repeating part5setup="import numpy as np; na = Np.arange (+)",#Setup runs only once6number=10000)#Number of repetitions7GOOD_NP = Timeit.timeit ('Na.dot (NA)',8setup="import numpy as np; na = Np.arange (+)",9number=10000)Ten  One Print('Native Run time:', Normal,'\ n', A       'Original NumPy run time:', NATIVE_NP,'\ n', -       'use the NumPy to bring your own function:', GOOD_NP)

Native run time:     1.236690534016816  original NumPy run time: 1.1835122400079854  using NumPy self-function: 0.02045012399321422

"Python" Machinelearning Machine Learning Introduction _ Efficiency Comparison