Playground
Explore training neural networks through hands-on practice with weight initialization, backpropagation, and iteration. Learn the impact of zero and random weights on accuracy and network behavior as you deepen your understanding of training dynamics.
We'll cover the following...
We'll cover the following...
Revision
Before we move on, let’s practice with the code for a little while. That’s optional, but it’s a good way to revise these concepts.
Go through all the codes which we have covered in this chapter by launching the below app:
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Hands-on challenge
In Fearful Symmetry, we learned that we should not initialize all the neural network’s weights to the same value. We may easily notice what happens if we ignore that advice. We can use NumPy’s zeros() function to initialize all the weights to . For example, ...