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In this quick walkthrough, I show the 5 components every neural network uses: Data – the inputs and targets Model – a simple nn.Linear layer Loss function – MSE to measure error Optimizer – SGD to update parameters Training loop – forward pass → loss → backward → update We generate simple data (y = 2x + 3), train a linear model ...
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