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For this assignment we had to use a dataset of everyday objects and classify it by training and using a neural network.

Steps

  1. Explore the CIFAR10 dataset: CIFAR-10 and CIFAR-100 datasets
  2. Set up a training pipeline to train a neural network on a GPU (using Kaggle).
  3. Experiment with different network architectures & hyperparameters.

Link to the Jupyter notebook I made for the assignment: remusa/03-cifar10-feedforward | Jovian

Reference Links

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