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The Deep Learning with PyTorch Workshop

You're reading from   The Deep Learning with PyTorch Workshop Build deep neural networks and artificial intelligence applications with PyTorch

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781838989217
Length 330 pages
Edition 1st Edition
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Author (1):
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Hyatt Saleh Hyatt Saleh
Author Profile Icon Hyatt Saleh
Hyatt Saleh
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Toc

4. Convolutional Neural Networks

Activity 4.01: Building a CNN for an Image Classification Problem

Solution

  1. Import the required libraries:
    import numpy as np
    import torch
    from torch import nn, optim
    import torch.nn.functional as F
    from torchvision import datasets
    import torchvision.transforms as transforms
    from torch.utils.data.sampler import SubsetRandomSampler
    from sklearn.metrics import accuracy_score
    import matplotlib.pyplot as plt
  2. Set the transformations to be performed on the data, which will be converting the data into tensors and normalizing the pixel values:
    transform = \
        transforms.Compose([transforms.ToTensor(), \
                            transforms.Normalize((0.5, 0.5, 0.5),\
                            ...
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