I have been recommended to use GitHub for all my coding projects as it is a great way to demonstrate to employers what you have been working on as well as just sharing anything you have created that might be useful to others. So I am storing my code for Neural Network Models I am working in a GitHub repository but I am not sure when I download a data set to run a test with where I should download that too? Inside or outside the git repository?

Sorry if this is a dumb question but new to this. I can imagine arguments for either answer. Mainly size being too big or the results being easily reproducible.


If the dataset isn't too large, you may add datasets on GitHub itself. Generally project datasets aren't large, but again, I can't be sure as you haven't mentioned any approximate size. But if it is large, you may refer to data source in your ReadMe or within your .py file as an external hyperlink.

For example, save dataset on Google Drive & turn on Viewable option by generating shareable URL. Now that generated link can be refered to in your ReadMe file as something like: "Kindly refer this external link to access dataset". Alternatively, you may also read data directly within your .py file from that generated link, and any project reviewer would notice that external link being used to read dataset.

Hope that answers your query!

  1. Upload dataset inside repository
  2. Upload on drive and attach the link, change the sharing settings to visible to all
  3. Directly provide source link if available

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