As simple as that. A set of my own notebooks, sometimes simply serving the purpose of following some tutorial (or as a place to take notes) and at other times digging a bit deeper:
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Anniversary: analysis of ~75K text phone messages exchanged with my partner. Reddit for more ideas =)
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Pandas vs. Numpy (matrix dot product) & Word Embeddings: performance comparative between Pandas and Numpy on a very specific operation -
dot
product - (to compute similarity between word embeddings). Reddit and Medium posts. -
MNIST: yet another MNIST tutorial. You won't find anything new here, I was just getting familiar with Tensorflow. However, what I don't usually find in other tutorials are practical ways to save / restore models or even to feed an individual photo and predict its class. So I made sure that I was trying all this stuff, plus a naive reflection in the end on how deep learning works 🤖 versus how we humans 👴 learn/model_knowledge.
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Automata: exploring Automata (and Turing Machines) theory through a series of examples and exercices.
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Python Unicode, how to avoid UnicodeEncodeError?: Tired of the freaking “UnicodeEncodeError: ‘ascii’ codec can’t encode character u’\motherf++++++’ in position 69: ordinal not in range(128)“ error message?
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Interesting concepts: a simple list of (useful?) concepts I don't want to forget.
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Euler's number: I just like Euler's number... wanna add cool facts about e? Fork it and share!
And remember, if you don't like Jupyter notebooks you can always export them as Python scripts:
jupyter nbconvert --to script <name of the notebook>