MicroGrad.jl: Part 5 MLP
Read OriginalThis article is the fifth part of a series on implementing automatic differentiation in Julia. It demonstrates how the MicroGrad.jl package can serve as the backbone for a machine learning framework, similar to Flux.jl. The tutorial walks through creating a multi-layer perceptron (MLP), implementing layers like ReLU and Dense, and training the network on the non-linear moons dataset for classification.
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