I spent a few hours yesterday until I finally made it work, so I figured out it worth spending time documenting how to get it done for others who might face the same issues that I encountered, and also for myself, since I will probably want to redo it on other containers in the future.
For me, the benefit of being able to attach to a running container on a remote host, was using the remote container as a development environment, while still using vscode from my computer as usual.
This is the 3nd article in our MAFAT Radar competition series, where we take an in-depth look at the different aspects of the challenge and our approach to it.
If you want a recap, check out previous posts: the introduction and the dataset.
As we already discussed, the two major issues with the provided dataset are:
In order to improve the result of the model, we needed to find more relevant data. One of the common ways of doing it in machine learning is through the use of…
In this post you will learn a very efficient way to use Colab when working on a project that will allow you control the files locally on your own computer.
I will show you how to do it when the project is maintained in a git repository, (even a private git repository), so that you can handle all the git actions easily from your computer as you are already used to.
I will share with you the code and file structure that I use that allows a quick initialization of the Colab notebook.
The benefits that I see when using…
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