Sklearn

We're going to use a package called sklearn to make the coding portion of this tutorial easier. Read this page to learn how to install it and when to use it.

Installation

In this tutorial, we will be using sklearn. Fortunately, installation is simple! Please run the following command in terminal or command prompt:

python3 -m pip install sklearn

When to use Sklearn

There are a lot of ML algorithms out there, and literature on the internet can be very dense. This is where sklearn comes in super handy! sklearn is a package you can install, and it has machine learning algorithms implemented and ready to go for whatever your ML needs may be. It also has relatively short and to the point descriptions of what each algorithm does. This is great if you want to play around with a bunch of algorithms with low overhead and see how they work.

sklearn is an extremely powerful tool. If you want to do digit recognition, you can literally make one function call on the right set of data and boom. You're done! However, you will only get credit for code that you write on your own. That being said, there are two main ways that you can use sklearn on your term project. One option is to use an algorithm from sklearn and have other complex code components that you write yourself. Another option is to use sklearn to find an algorithm that does what you want, and then implement it on your own. What you write yourself may not be as accurate as the sklearn version, but if it works at all that really is something you can put on a resume!