Beginner ML: Installing Acaconda & Jupyter Notebook
Getting Anaconda and Jupyter Notebook up-and-running on your machine is a quick-and-easy way to get started with machine learning.
Created on April 16|Last edited on April 17
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One of the easiest ways to get started with machine learning is by writing your scripts in Google Colab. There are big advantages to it, such as being very easy to use, easy to share, and it comes packed with many of the libraries you'll want to use.
But at some point you may expand beyond the technical limitations of Colab, you way want to run certain projects on your own machine, or you might want to do things that you just can't in Colab.
If you're at this point in your evolution or just want to start with Notebooks instead of Colab (good call IMO - though I started with Colab) then this is for you, and we'll get you setup in just a few minutes.
Here's what we'll be covering:
Setting Up Anaconda
This part might look a little frightening for those who don't work in the command line much, but I promise it's as easy as copy-and-paste.
First, we're going to install Anaconda. Anaconda is a distribution of Python that includes a bunch of packages and libraries - including Jupyter.
It does other things, like letting you create an environment to run your scripts in that are independent of others, but we won't be using those other features today.
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And install. When prompted you'll avoid adding the page by not checking the top box at, but copy the destination path as pictured in the image below.
And when you get to the part where it's choosing a destination path:
In this case, it's C:\ProgramData\Anaconda3 you'll need to copy down.
Once that's completed you'll need to take a moment to add a path to the environment variables. To do this head to your search bar again and type environment variables.
And select "Edit the system environment variables".
Select "Path" and choose "Edit".
You'll then copy in the path like:
And click OK.
And now you're ready to use Jupyter, which makes everything else much easier in my opinion.
Getting Started With Jupyter Notebooks
To launch Jupyter to actually start playing with GPT-3 we need to open the command line, and type jupyter notebook, and then Enter.
You'll notice that I clicked "New" and started a new Python 3 notebook. You'll want to do the same.
Which should leave you with a screen that looks like:
One of the great things about Jupyter Notebooks is that like Colabs, you can add your own comments and context in markdown fields:
If you've never used Colabs or Jupyter before there's a nice quickstart here. And a refresher on key markdown here.
And ready to get started on your project!
If you're ready to head off to work on the project that brought you hear in the first place, I hope you'll bookmark it and come back and I'll be updating the reports below with some fun projects aa I write them up. :)
Fun Beginner ML Projects
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