Template code for the machine learning unit of the cs474/cs573 computer vision course at Clarkson University. This repository provides a script to download the training data and template files that you can use to help with training (though you're not required to use them).
We're going to use GitHub codespaces for coding a code execution.
If you don't already have one, register for a GitHub account.
Then create a new private GitHub repository. Click "New".
Give it a good name. Select "Private" for visibility, and add a README file.
Once you've created the repo, open the "Code" menu, select "Codespaces", and "Configure dev container".
- Create a new codespace by visiting this page.
- Click "New codespace" at the top right.
- Create a new codespace with your private GitHub repository as the source repo.
You should now have access to your own codespace with a file explorer and terminal. More about GitHub codespaces.
Create a new file called hello.py.
Create your hello world codeblock.
print("hello world!")Execute your code in the terminal
@nikwl ➜ /workspaces/codespaces_test (main) $ hello.py
hello world!Install new dependencies using pip install.
