Convolutional Neural Networks (CNNs)

In this lab, we learn how to create and train a Convolutional Neural Network (CNN) using PyTorch.
The main goal is to classify images from the CIFAR-10 dataset and compare the performance of Fully Connected Networks (FCN) and CNNs.

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Key Topics

• Basic PyTorch operations
• Understanding CNN architecture and components
• Loading and preprocessing image data
• Building and training a simple CNN
• Evaluating performance on a test set
• Using pre-trained models for image classification

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Tools & Libraries

• Python
• PyTorch
• torchvision, torchsummary
• NumPy, Pandas
• Matplotlib, scikit-learn

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