Question: Consider two one-dimensional Gaussian distributed classes that have a common variance equal to 1. With means of mu(1) = -10 and mu(2) = 10. These

Consider two one-dimensional Gaussian distributed classes that have a common variance equal to 1. With means of mu(1) = -10 and mu(2) = 10. These two classes are essentially linearly separable. Design a classifier that separates these two classes.

Please draw a directed graph and estimate good weights/biases for a simple neural network implementation.

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