Deep Learning with elixir This project is called Deep Pipe(DP) Network example (See test.ex) defnetwork init_network2(_x) do _x |> f(5,5) |> flatten |> w(576,100) |> b(100) |> sigmoid |> w(100,10) |> b(10) |> sigmoid end Usage: iex -S mix module DP is Deep Pipe(DP) module module DPB is DP for batch module DPP is DP for parallel module Tensor is code for CNN data operation module Dmatrix is code for Matrix module Pmatrix is code for Matrix product in paralell module MNIST is code for MNIST data set I implemented backpropagation and numerical-gradient Now I'm testing small data set. expample: iex(1)> require Time Time iex(2)> Time.time(Test.adagrad(100,50)) preparing data ready 0.44383196477296905 0.37511510344740406 0.42960276053222174 0.352539961358792 0.2861907950783934 0.21772105559847485 0.1880808136708525 0.14605224305760664 ... 0.016682469588708566 0.019254450344041836 0.00594231528389093 0.013773451908515 0.019834342678945693 accuracy rate = 0.88 "time: 202819950 micro second" "-------------" :ok >