Set up your machine learning journey efficiently by integrating Google Colab with your Jupyter Notebooks. Learn the straightforward steps to seamlessly connect Google Drive, enabling convenient cloud-based access to your Python machine learning files.
Key Insights
- Download the provided class files and upload the initial Jupyter Notebook—ml10 stats start—to Google Colab, ensuring all materials are stored and accessed in the cloud.
- Establish a connection between Google Colab and Google Drive by executing the first code cell, authorizing file access permissions for seamless workflow going forward.
- Using Google Colab and Google Drive consistently will enable you to conveniently access, manage, and run Jupyter Notebooks from any location or device.
Note: These materials offer prospective students a preview of how our classes are structured. Students enrolled in this course will receive access to the full set of materials, including video lectures, project-based assignments, and instructor feedback.
Hello everybody, we're going to walk through our setup how to get started with our class files So the very first thing you're going to do is download our class files Should come in a zip archive that you can extract once you've got a folder What we're going to do is we're going to use Google Colab to open the very first Jupyter Notebook And we'll talk about what a Jupyter Notebook is momentarily But you are going to want to be using Google Colab and Google Drive all our examples We'll use that setup and it's a good setup. That's why we're using it so you'll get to know Google Colab and how it works and You'll be able to use your Jupyter notebooks on any machine because they'll live in the cloud
Okay, let's walk through what that process looks like just for getting started It should be easier from then on but just for getting your files into your account on Google Colab and Google Drive So the very first thing you should do is go to Google Colab And once you're there, it first prompts you for to open a notebook. We're gonna choose upload and browse And then you're gonna navigate your way to your folder, which should be called Python machine learning bootcamp To the start folder within there and let's open up ml10 stats start That's the first notebook we'll be working with When you choose open Google Colab will upload that file and now it's a part of your Google Colab collection.
So Once you're there one of the very first we'll actually cover some material in a moment But in terms of getting this started our very first cell block our very first code cell is this one that Sets up a connection between your Google Colab and your Google Drive So I'd like you to run that cell and you do that by pressing the start button It's going to take a moment and then it's going to prompt you to connect Google Drive to This particular notebook, but let's do that. Let's see what that looks like It's like it's getting Python started which always takes about you know 10-15 seconds the first time that you run it in that you run a new notebook Didn't even take that long. Then you're going to get this message to permit your this notebook to access your Google Drive files You'll get this message for each one if you haven't set up a Google Drive Colab connection before this process will be slightly more complicated.
It'll just have a little checkbox You'll choose select all and you'll choose you'll give Google all the permissions to access from Google Colab your Google Drive files Once you've done it the first time it looks just like this just a couple of continue buttons and Then this should get a little check mark. This gets a check mark. It means that your Google Colab and your Google Drive are connected Now they're that they're connected We can Upload all of our files at the same time to Google Drive and be able to access them and be able to switch over to Google Colab for any notebook files.
Let's do that in the next video