Part 7: Backward Pass
Up to this point, We have built a 'Forward Pass' that makes predictions, and a 'Loss Function' that measures exactly how far off those predictions are. In order to enable our model to learn patterns f
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Up to this point, We have built a 'Forward Pass' that makes predictions, and a 'Loss Function' that measures exactly how far off those predictions are. In order to enable our model to learn patterns f
In our previous part, we witnessed a "numerical explosion." Because our target formula involves x³, the raw values reached into the thousands, causing our loss to skyrocket into the millions. To build
With our dataset prepared and our model's architecture ready, we are at starting point of deep learning. The first part is the forward pass. In this part, we will implement the entire forward pass fro
So far, we have implemented our dataset, layers, and an initializer. Now, it’s time to combine them and start shaping an actual neural network. Before we get to the code, let’s first walk through the