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Apr 25th, 2019
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  1. import sys
  2.  
  3. ####################
  4. ### Set the hyperparameters in you myanswers.py file ###
  5. ####################
  6.  
  7. from my_answers import iterations, learning_rate, hidden_nodes, output_nodes
  8.  
  9. N_i = train_features.shape[1]
  10. network = NeuralNetwork(N_i, hidden_nodes, output_nodes, learning_rate)
  11.  
  12. losses = {'train':[], 'validation':[]}
  13. for ii in range(iterations):
  14. # Go through a random batch of 128 records from the training data set
  15. batch = np.random.choice(train_features.index, size=128)
  16. X, y = train_features.ix[batch].values, train_targets.ix[batch]['cnt']
  17.  
  18. network.train(X, y)
  19.  
  20. # Printing out the training progress
  21. train_loss = MSE(network.run(train_features).T, train_targets['cnt'].values)
  22. val_loss = MSE(network.run(val_features).T, val_targets['cnt'].values)
  23. sys.stdout.write("\rProgress: {:2.1f}".format(100 * ii/float(iterations)) \
  24. + "% ... Training loss: " + str(train_loss)[:5] \
  25. + " ... Validation loss: " + str(val_loss)[:5])
  26. sys.stdout.flush()
  27.  
  28. losses['train'].append(train_loss)
  29. losses['validation'].append(val_loss)
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