W1
Module 1: The Mathematical Engine of Neural Networks
By the end of this module you will be able to explain and implement the core mathematical concepts required for backpropagation, including multivariate calculus (gradients, chain rule) and basic linear algebra.
3 videos•58m
3 readings
3 topics
1 homework
W2
Module 2: Implementing Backpropagation from Scratch
By the end of this module you will be able to build and train a simple two-layer neural network from scratch using only NumPy, correctly implementing the forward pass, loss calculation, and the backpropagation algorithm.
4 videos•44m
3 readings
4 topics
1 homework
References
Week 1: Module 1: The Mathematical Engine of Neural Networks
Week 2: Module 2: Implementing Backpropagation from Scratch
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