Ch-1-Neural-Networks○Activation Functions○The Artificial Neuron○Backpropagation○Forward Propagation○Multi-Layer Perceptron (MLP)○Multi Layer Perceptrons○PerceptronCh-2-Training-Deep-Networks○Batch Normalization○Dropout○Learning Rate Schedules○Loss Functions○Optimizers○Weight InitializationCh-3-Practical-Deep-Learning○Building Models○Experiment Tracking○Model Evaluation○PyTorch Basics○Saving & Loading Models○The Training Loop○Training Pipelines
Ch-1-Neural-Networks○Activation Functions○The Artificial Neuron○Backpropagation○Forward Propagation○Multi-Layer Perceptron (MLP)○Multi Layer Perceptrons○Perceptron
Ch-2-Training-Deep-Networks○Batch Normalization○Dropout○Learning Rate Schedules○Loss Functions○Optimizers○Weight Initialization
Ch-3-Practical-Deep-Learning○Building Models○Experiment Tracking○Model Evaluation○PyTorch Basics○Saving & Loading Models○The Training Loop○Training Pipelines