This repo contains papers and notebooks for my studies.
- https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/
- https://ml-cheatsheet.readthedocs.io/en/latest/activation_functions.html
- https://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=spiral®Dataset=reg-plane&learningRate=0.01®ularizationRate=0&noise=0&networkShape=7,2&seed=0.79129&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=true&xSquared=true&ySquared=true&cosX=false&sinX=true&cosY=false&sinY=true&collectStats=false&problem=classification&initZero=false&hideText=false
- https://ruder.io/optimizing-gradient-descent/
- http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
- http://www.deeplearningbook.org/
- https://leonardoaraujosantos.gitbook.io/artificial-inteligence/