Why not pie throughout the section we're going to explore this popular library called mom pie which
are very similar to Python lists.
It's one of the most used and popular libraries when it comes to data science and machine learning.
But I want to ask you why do we need this don't we have Python lists.
Why is not pie so popular and a must use tool for machine learning.
There are two main reasons why we want to use num PI for our problems.
You see under the hood many functionalities that num pi offers us are actually written in C a programming
language that is really really fast.
If we used Python lists it would actually be a lot slower to do some of the things that we're about
to do so num pi operations on arrays and lists are a lot faster than performing the same operations
in Python and as you'll find out when it comes to machine learning.
We do a lot of computation.
We do a lot of processing and that's why GP use or graphical processing units are used because so many
calculations need to happen.
So we need to have any possible performance advantage we can which num pi offers the second reason we
want to use something like num pi is that when it comes to machine learning.
Well machines usually only understand ones and zeros and things like numbers which can be contained
and num pi are really easy for machines to understand versus something more complicated.
For example an image can be represented in numbers where a number represents the colour of a pixel.
And we'll see later on the course where we try and convert different fields different attributes into
numbers.
For example if a patient has heart disease instead of yes or no we convert it to 1 or 0 this idea of
converting data into something that a machine can understand like numbers like binary like ones in 0
allows us to make machines learn that's how machines learn machines learn by performing multiple operations
and by storing this information in an array like num pi is a great way for us to represent that data
from what humans can understand to what computers can understand but you'll see that as we progressed
more and more through the course for now let's get started.