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DPS921/PyTorch: Convolutional Neural Networks

4 bytes added, 12:39, 29 November 2020
Implementation of Neural Network
''' 2. Download the needed datasets from the MNIST API, partition them to feasible data
train = datasets.MNIST('', train = True, download = True, transform=transforms.Compose([transforms.ToTensor()])) test = datasets.MNIST('', train = False, download = True, transform=transforms.Compose([transforms.ToTensor()]))
trainset = torch.utils.data.DataLoader(train, batch_size = 10, shuffle = True) testset = torch.utils.data.DataLoader(test, batch_size = 10, shuffle = False)
== Getting Started With Jupyter lab ==

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