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Derivatives and gradients: the one calculus lesson ML actually uses
Machine learning can look like a huge collection of algorithms, architectures, and optimization tricks. Underneath most of them, however, sits one compact idea:
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Backpropagation demystified: hand-compute the gradients, then verify with autograd
Backpropagation is the engine behind modern deep learning. Whether you’re training a tiny multilayer perceptron or a frontier-scale language model, every optimization step depends on efficiently compu