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Our subset of Tiny ImageNet contains 30 different categories, we will refer to it as TinyImageNet30. The training set has 450 resized images (64x64 pixels) for each category (13,500 images in total). \n\n## Required Packages 📦\n* numpy\n* h5py\n* matplotlib\n* pytorch\n\n## How the work has been divided 👩🏻‍💻\n1. Function Implementation - to get the datasets and the dataloaders\n2. Function Implementation - model class for a simple MLP and CNN Model\n3. Model Training\n4. Generating Confusion Matrices and ROC\n5. Implementing strategies to tackle overfitting\n6. Model Testing\n7. 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