Explore tensors, autograd and feed-forward networks, culminating in hand-calculated backpropagation training.
Overview
Syllabus
- Unit 1: Building a Single Neuron
- Unit 2: Activation Functions Explained
- Unit 3: Neuron Output in Action
- Unit 4: Stacking Neural Network Layers
- Unit 5: Architecting a Network
- Unit 6: Loss Functions and Gradients
- Unit 7: Backpropagation Step by Step
- Unit 8: The Training Loop in Focus
- Unit 9: Gradient Descent Methods
- Unit 10: Overfitting and Underfitting
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