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Implementation of several (hopefully) ML papers without ML libs

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No lib ML

The goal of this project is to implement various ML papers (hopefully) without usage of any pre-done ML algorithms.

Such thing might be usefull in case you want to get deeper understanding of the process, standing behind the symbols in the paper (or in some cases just understand what does them mean).

Installation guidelines

You could just view the contents of the notebook inside github preview, or you might want to try it out on your PC.

In last case you would need to install the jupyter and the math/visualization libraries used by the project. To do this, users of the pip need to run these two commands:

pip install notebook

(To install jupyter)

pip install -r requirements.txt

(To install other libraries required (check their list, that might change from commit to commit, in requirements.txt file))

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