Calculus for ML Checkpoint

Derivatives, gradients, and chain rule.


Get every question correct to pass this checkpoint. You can review feedback, revise your answers, and submit again.

1. For L=(3w-2)^2 at w=1, what is dL/dw?

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2. For f(x,y)=x*y+y^2 at (2,3), what is the partial derivative with respect to y?

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3. At a parameter value the gradient is -4. One gradient-descent step with learning rate 0.1 changes the parameter by:

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4. For f(x)=x^3, what is the derivative at x=-2?
5. A differentiable loss has zero gradient at w. What can you conclude without more information?

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