First attempt writing a neural network, using the MNIST dataset, to detect handwritten numbers.
I read the first two chapters of neuralnetworksanddeeplearning.com then attempted the MNIST challenge myself using the notes I took from the book.
src/mnist_loader.py is a direct copy from from neuralnetworksanddeeplearning.com
atomicwrites 1.2.1 py27_0
attrs 18.2.0 py27h28b3542_0
blas 1.0 mkl
ca-certificates 2018.03.07 0
certifi 2018.10.15 py27_0
funcsigs 1.0.2 py27hb9f6266_0
intel-openmp 2019.1 144
libcxx 4.0.1 hcfea43d_1
libcxxabi 4.0.1 hcfea43d_1
libedit 3.1.20170329 hb402a30_2
libffi 3.2.1 h475c297_4
libgfortran 3.0.1 h93005f0_2
mkl 2018.0.3 1
mkl_fft 1.0.6 py27hb8a8100_0
mkl_random 1.0.1 py27h5d10147_1
more-itertools 4.3.0 py27_0
ncurses 6.1 h0a44026_0
numpy 1.15.4 py27h6a91979_0
numpy-base 1.15.4 py27h8a80b8c_0
openssl 1.1.1a h1de35cc_0
pathlib2 2.3.2 py27_0
pip 18.1 py27_0
pluggy 0.8.0 py27_0
py 1.7.0 py27_0
pytest 4.0.1 py27_0
python 2.7.15 h8f8e585_4
readline 7.0 h1de35cc_5
scandir 1.9.0 py27h1de35cc_0
setuptools 40.6.2 py27_0
six 1.11.0 py27_1
sqlite 3.25.3 ha441bb4_0
tk 8.6.8 ha441bb4_0
wheel 0.32.3 py27_0
zlib 1.2.11 h1de35cc_3