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Exercise

Using DataLoader

The DataLoader class is essential for efficiently handling large datasets. It speeds up training, optimizes memory usage, and stabilizes gradient updates, making deep learning models more effective.

Now, you'll create a PyTorch DataLoader using the dataset from the previous exercise and see it in action.

Instructions

100 XP
  • Import the required module.
  • Create a DataLoader using dataset, setting a batch size of two and enabling shuffling.
  • Iterate through the DataLoader and print each batch of inputs and labels.