Close 3 deeplearning

[ampudia19]

Deep learning material (zero-to-hero style)

Checklist:

• [X] I have refactored my code out from notebooks/
• [X] I have checked the code runs
• [X] I have tested the code
• [X] I have run pre-commit and addressed any issues not automatically fixed
• [X] I have merged any new changes from dev
• [X] I have documented the code
  • [X] Major functions have docstrings
  • [X] Appropriate information has been added to READMEs
• [X] I have explained this PR above
• [X] I have requested a code review

[india-kerle]

Live comments as I work through the notebook:

• I LOVE the GIF in the notebook - nice touch 👍
• the text makes a ton of sense and the pace is nice
• the logistic regression example is really nice
• you mention saving models but then move to a different section - i would just reword slightly i.e. "We will see this methods in action later in the notebook." (which I've done and pushed to the branch)
• LOVE the surname origin multi-class prediction example
• the time series component to your bike demand prediction example has sent me
• I get FileNotFoundError: [Errno 2] No such file or directory: 's3://dap-taltech/data/images' for the images getter - i think its because you've written it loading in the file locally only. I've pushed the edits to allow for loading from s3 also!
• training the NN with image data takes a bit more time - i've added a comment in the tutorial to say it will takea bit of time.
• I've actually had a field day with your live updating plot_pooling and plot_convolution functions
• I would summarise the key goals of the tutorial again at the end of the notebook - i've added a markdown cell that re-iterates your learning goals

[india-kerle]

I've addressed the tiny comments i've made on language. The only major change i've made is related to the DataGetters class - otherwise, I'm going to merge into dev and address any utils related issues in a separate PR. Loved this tutorial - my fave so far :0