Python offers many libraries to work with, one of which is Numpy.
Here you will learn how Numpy offers support for large amounts of data, which will come in handy for your Job!
I have also added a link for NumPy Documentation.
NumPy has a number of key features that give it great advantages over Python lists. Below are a few convincingly strong features:
One such feature is speed. This speed comes from the nature of NumPy arrays being memory-efficient and from optimized algorithms used by NumPy for doing arithmetic, statistical, and linear algebra operations.
Another great feature of NumPy is that it has multidimensional array data structures that can represent vectors and matrices. NumPy is optimized for matrix operations and it allows us to do Linear Algebra operations effectively and efficiently, making it very suitable for solving machine learning problems.
NumPy has a large number of optimized built-in mathematical functions. These functions allow you to do a variety of complex mathematical computations very fast and with very little code (avoiding the use of complicated loops)
