How is a neural network similar to a computer network? How are they different?
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The graph that represents possible functions is shown in the diagram below. Point C shows the point on y-axis where f(x) and g(x) crosses. The result should be interpreted by the level of steepness of each slope
g(x) has a steeper gradient than f(x) and this indicates steeper fee rise for producing the T-shirt. So if Marissa is to choose the better value for her money to produce T-shirt, she should choose the function f(x) providing there are no other factors to consider other than prices.
g(x) has a steeper gradient than f(x) and this indicates steeper fee rise for producing the T-shirt. So if Marissa is to choose the better value for her money to produce T-shirt, she should choose the function f(x) providing there are no other factors to consider other than prices.