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DPS921/PyTorch: Convolutional Neural Networks

392 bytes added, 17:16, 29 November 2020
Implementation of a Neural Network
import torch.optim as optim
 
optimizer = optim.Adam(net.parameters(), lr=0.001)
 
EPOCHS = 3
print("Accuracy: ", round(correct/total, 3))
 
''' 7. View the data at index of 0 in the training data set as 28 x 28 Image, Making sure to import 'matplotlib'.
 
import matplotlib.pyplot as plt
plt.imshow(X[0].view(28,28))
plt.show()
 
''' 8. Test the trained neural network to check whether the digit value shown in the image is in fact the number
the neural network determined it to be.
 
print(torch.argmax(net(X[0].view(-1, 784))[0]))
== Getting Started With Jupyter ==

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