Master np.arange(), np.linspace(), and np.logspace() for sequence generation.
Use `np.arange` when you know the step size between points (stop is excluded). Use `np.linspace` when you know the total number of samples desired (stop is included).
`arange` is walking with a fixed ruler jump (step size). `linspace` is dividing a rope of given length into equal pieces (sample count).
`np.arange(start, stop, step)` halts before `stop`. `np.linspace(start, stop, num)` generates exactly `num` evenly spaced points including `stop`.
a = np.arange(0, 10, 2); l = np.linspace(0, 1, 5)a = np.arange(0, 10, 0.1) # Risk of floating point drifta = np.linspace(0, 10, 101)Using floating-point step in arange can cause inconsistent element counts due to IEEE 754 precision.
Solve the objective below using NumPy vectorized syntax
Generate an array of numbers from 0 up to 10 (exclusive) in steps of 2 using `np.arange` and print it.
[0 2 4 6 8]