anchor.diff:  let rec train
    epoch
    netAcc
  - ((training_samples:List<List<float>>), (teaching_inputs:List<List<float>>))
  - ((testing_samples:List<List<float>>), (teaching_testing_inputs:List<List<float>>))
  + ((training_samples:List<List<float>>), (teachingInputs:List<List<float>>))
  + ((testing_samples:List<List<float>>), (testOutputs:List<List<float>>))
    =
    let trainOnce = feedForward >> backPropagate
   
  
positive.code: ﻿
  /// Matrix Transpose.
  let transpose xss =
   let rec f xss acc =
  
negative.code:   let training_index = [0..(training_samples.Length - 1)]
    let training_rand_index = shuffleList training_index.Length rand training_index
    let shuffled_training_s = dataAtIndex training_samples training_rand_index
    let shuffled_training_i = dataAtIndex teachingInputs training_rand_index
  
    let testing_index = [0..(testing_samples.Length - 1)]
    let testing_rand_index = shuffleList testing_index.Length rand testing_index
    let shuffled_testing_s = dataAtIndex testing_samples testing_rand_index
    let shuffled_testing_i = dataAtIndex testOutputs testing_rand_index
  
    let trained = List.fold2 (funcNet trainOnce) netAcc shuffled_training_s shuffled_training_i
    let rms_trained_err = networkDistance trained
  