Backpropagation: One Training Step by Hand
This lesson is part of the course
In this lesson
You run one full backpropagation step for one Lumora customer: error signals, all nine gradients via the chain rule, the weight update, and you watch the loss fall.
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Lessons in this course
- A Single Neuron: Weighted Sum + Bias Locked
- Activation Functions: Step, Sigmoid, tanh & ReLU Locked
- Forward Pass of a 2-2-1 Network Locked
- Loss Functions: MSE vs Cross-Entropy Locked
- Backpropagation: One Training Step by Hand Locked
- Learning Rate: Five Steps, Three Speeds Locked
- Softmax & Multi-Class Probabilities Locked
- Overfitting: Train vs Test Error & Early Stopping Locked