As noted above, NumPy arrays behave a lot like other Python objects, for the sake of convenience. For instance, they can be indexed like lists; arr[0] accesses the first element of a NumPy array.

However, before we clap ourselves on the back and move on, can we go even faster? Let's change our script a bit and replace the Python list with a NumPy array: import numpy as np list = ...

NumPy is known for being fast, but could it go even faster? Here’s how to use Cython to accelerate array iterations in NumPy. NumPy gives Python users ... but the difference should be clear.

NumPy arrays require far less storage area than other Python lists, and they are faster and more convenient to use, making it a great option to increase the performance of Machine Learning models ...