Introduction to Numpy

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TRANSCRIPT

Hello everyone and welcome to our course on an Introduction to Numpy. My name is Nimish and I'll be guiding you through the next hour or two, in which we'll be learning how to use the Numpy library to build and use powerful arrays. So let's start with what is Numpy? What are we getting ourselves into here? Well Numpy is simply a library written in C but used in Python, that contains data structures and functionality that will allow for the usage of powerful and functional arrays and matrices. Numpy arrays and matrices are widely used in data science, machine learning, and game development fields, and pretty much anywhere else a coder wants a more powerful and functional array than the basic list.

So why learn Numpy then? Well Numpy arrays are many, many times than regular lists in Python. Numpy arrays also have a ton of extra functionality built right into these data structures. And that makes for very highly efficient mathematical computation. Numpy arrays are widely used in many prominent and upcoming fields like some of the ones I mentioned. So knowing how to use them will be very highly advantageous. And pretty much for those of you who wants to go into data science, machine learning, or any of these such fields, learning Numpy is a must, as Numpy arrays go very well with a lot of these fields.

Who should be taking this course? This course is meant for people who are completely new to Numpy. And generally people who don't have a ton of experience working with matrices or specialized arrays. We are expecting that you have some experience with the Python programming language and those of you who do want to go on to data science or machine learning fields, you will find this especially useful. Like I said, you'll see Numpy arrays, matrices pop up all the time when you're writing data science or machine learning programs. So what kind of topics are we going to be covering in this tutorial? Well first we'll start by downloading and installing Anaconda and Jupiter. Anaconda is simply a package manager. And we'll be using Jupiter notebooks, which is kind of like an online interactive Python notebook that will allow us to write and run efficient Python code.

The next topic will be on first Numpy arrays, then Numpy matrices. We will follow a similar format first talking about how to create Numpy arrays. Then we'll talk about some fetch operations. These will be functions that will allow us to retrieve elements or attributes and then modification operations. And then we'll finish up Numpy arrays by talking about a real practical example. We'll be doing pretty much the same with matrices but instead of creating Numpy arrays, we'll ... https://www.youtube.com/watch?v=jS6o4NgK89M