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ANN Workshop for PyConUK 2019
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.gitignore initial commit for the workshop, still lots to do Sep 10, 2019
01-intro.ipynb full workshop - at least as much as can be done in the time given Sep 12, 2019
02-concepts.ipynb
03-concepts-exercises.ipynb
04-concepts-exercise-solutions.ipynb full workshop - at least as much as can be done in the time given Sep 12, 2019
05-pulsars.ipynb full workshop - at least as much as can be done in the time given Sep 12, 2019
06-weights-exercises.ipynb
07-weights-exercise-solutions.ipynb
08-training.ipynb full workshop - at least as much as can be done in the time given Sep 12, 2019
09-autograd-exercises.ipynb
10-autograd-exercise-solutions.ipynb full workshop - at least as much as can be done in the time given Sep 12, 2019
11-autograd-ann.ipynb full workshop - at least as much as can be done in the time given Sep 12, 2019
12-autograd-dag.ipynb
13-ann-scratch.ipynb full workshop - at least as much as can be done in the time given Sep 12, 2019
LICENSE initial commit for the workshop, still lots to do Sep 10, 2019
README
README.md
ann.svg full workshop - at least as much as can be done in the time given Sep 12, 2019
autograd.svg initial commit for the workshop, still lots to do Sep 10, 2019
crown-scaled.svg initial commit for the workshop, still lots to do Sep 10, 2019
graph-ann.svg
perceptron.svg
preparation.svg
pulsars_raw.csv
pulsars_tuned.csv initial commit for the workshop, still lots to do Sep 10, 2019
scratch.svg initial commit for the workshop, still lots to do Sep 10, 2019

README.md

README for nnag

Description

Workshop on a simplified neural network library. The talk is heavily inspired by autograd and pytorch.

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Copyright (C) 2019 Michal Grochmal

This file is part of nnag, which is distributed under the MIT license.

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