I have an older ’09 Macbook Pro and had trouble while trying to run the latest Keras to use for my latest Flatiron school neural network projects. The older Mac only updates to El Capitan, so it’s unable to run the latest versions of Keras in Jupyter notebooks. To get around this, I have been trying to integrate the use of Google Colab with my workflow. Colab is a cloud-based notebook and has the needed updates to run Keras and has come in handy. Trying to learn the small differences between Jupyter notebooks and Colab in order to keep everything flowing smoothly and all my changes synced has been challenging. Here is a little workflow that I’ve found useful in managing my notebooks and Github repositories. It’s not the most elegant but I have found it to be useful and it gets the job done for now, while I continue to learn more about using Colab and all of it’s connections to Github.

1. Create a repository in Github.

If you already have a repository you want to work with, then move to step two of this process to create or open a Colab notebook. If you need to make a whole new repository to start with, go to Github and create a new one. Click the green “New” button under the repository section.

Click the green button to create a new repo.

Add a name for the repository on the next screen, and click the box to initialize a README. You can choose to add a license to the repository, though I am still learning about all of the different types there are and won’t go into detail about that in this article. Here’s a good link I found about the differences between some of them for you to check out. https://www.fastcompany.com/3014553/what-coders-should-know-about-copyright-licensing. Then click “create repository”.

The next screen will be a sort of blank slate repository which shows your README file which you can leave alone for now and head over to Google Drive.

#google-colab #python #jupyter-notebook #mac #github