Activation Functions Attention Mechanisms & Transformers Autograd Convolutional Neural Networks (CNNs) Custom Autograd Functions & Hooks Data Augmentation Datasets & DataLoaders Debugging & Profiling PyTorch Models Distributed Training & Multi-GPU Generative Models (GANs & VAEs) GPU/CUDA Hyperparameter Tuning Learning Rate Scheduling Mixed Precision Training (AMP) Model Evaluation & Metrics Neural Network Layers & Building Blocks (Conv, Pooling, BatchNorm, Dropout) nn.Module & Models ONNX Export & Interoperability Optimizers & Loss Recurrent Neural Networks & LSTMs Regularization Techniques Saving & Loading Tensors TorchScript & Model Deployment Training Loop Transfer Learning Visualization with TensorBoard