In PyTorch, a DataLoader is a tool that efficiently manages and loads data during the training or evaluation of machine learning models. It acts as a bridge between datasets and models, facilitating seamless data handling throughout the process. In this tutorial, we'll explore how to utilize PyTorch's DataLoader with synthetic and classical MNIST datasets, covering the following topics:
- Understanding DataLoader
- Usage with simple data
- Usage with MNIST Dataset
- Conclusion
Let's get started.