- Build and train neural networks using PyTorch.
- Hands-on implementation of CNNs, RNNs, autoencoders, and GANs.
- Visualize training curves and filter outputs for better intuition.
- Learn hyperparameter tuning, batch normalization, and dropout.
- Focus on understanding why models work or fail in practice.
