For this assignment we had to use a dataset of everyday objects and classify it by training and using a neural network.
Steps
- Explore the CIFAR10 dataset: CIFAR-10 and CIFAR-100 datasets
- Set up a training pipeline to train a neural network on a GPU (using Kaggle).
- Experiment with different network architectures & hyperparameters.
Link to the Jupyter notebook I made for the assignment: remusa/03-cifar10-feedforward | Jovian