Autoencoder in PyTorch - Theory & Implementation

Learn how Autoencoders work and implement them in PyTorch in this 30-minute deep learning tutorial. Explore the theory behind Autoencoders, then dive into practical implementation with PyTorch. Cover data loading techniques, build a simple Autoencoder, create a training loop, and visualize results by plotting images. Advance to constructing a CNN Autoencoder, gaining hands-on experience with more complex architectures. Conclude with an exercise to reinforce your understanding and apply newly acquired skills. Ideal for those looking to deepen their knowledge of deep learning techniques and PyTorch implementation.

- Theory
- Data Loading
- Simple Autoencoder
- Training Loop
- Plot Images
- CNN Autoencoder
- Exercise For You