np.linspace allows you to define how many values you get including the specified min and max value. It infers the stepsize:
>>> np.linspace(0,1,11)
array([0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ])
np.arange allows you to define the stepsize and infers the number of steps(the number of values you get).
>>> np.arange(0,1,.1)
array([0. , 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
contributions from user2357112:
np.arange excludes the maximum value unless rounding error makes it do otherwise.
For example, the following results occur due to rounding error:
>>> numpy.arange(1, 1.3, 0.1)
array([1. , 1.1, 1.2, 1.3])
You can exclude the stop value (in our case 1.3) using endpoint=False:
>>> numpy.linspace(1, 1.3, 3, endpoint=False)
array([1. , 1.1, 1.2])