NumPy Optimization: Vectorization and Broadcasting | Paperspace Blog`

Libraries that speed up linear algebra calculations are a staple if you work in fields like machine learning, data science or deep learning.  NumPy, short for Numerical Python, is perhaps the most famous of the lot, and chances are you've already used it. However, merely using NumPy arrays in place of vanilla Python lists hardly does justice to the capabilities that NumPy has to offer.


This is a companion discussion topic for the original entry at https://blog.paperspace.com/numpy-optimization-vectorization-and-broadcasting

This code may need slight changes as
def mul_list(l1, l2):
for i, j in zip(l1, l2):
i * j
in currrent form, it may give error as " list indices cant’t be tuple "