Supervised Machine Learning Basics
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Questions and Answers

What is the value of the step size after 3 iterations of gradient descent?

  • 0.01787
  • 0.07626
  • 0.15753 (correct)
  • 0.03692

    • What is the value of the model parameter a after 5 iterations of gradient descent?

  • 1.28616
  • 1.23137
  • 1.15511
  • 1.26829 (correct)

    • What is the purpose of the gradient descent algorithm in this example?

  • To find the optimal value of the parameter a
  • To find the minimum value of the loss function J (correct)
  • To find the initial estimate of the parameter a
  • To find the maximum value of the loss function J

    • What is the value of the partial derivative of the loss function J with respect to the parameter a at iteration 1?

    <p>-67218.0000</p> Signup and view all the answers

    What is the value of the model parameter a after 10 iterations of gradient descent?

    <p>1.30201</p> Signup and view all the answers

    What is the formula for updating the model parameter a in the gradient descent algorithm?

    <p>a = a - (step size) * (∂J/∂a)</p> Signup and view all the answers

    What is the initial estimate of the model parameter a?

    <p>0</p> Signup and view all the answers

    What is the value of the step size after 10 iterations of gradient descent?

    <p>0.00098</p> Signup and view all the answers

    What is the purpose of the calculations in Table 3.2?

    <p>To test the understanding of the gradient descent algorithm</p> Signup and view all the answers

    What is the graphical representation of the gradient descent algorithm shown in Figure 3.9?

    <p>Red arrows indicate change in parameter value a at each iteration</p> Signup and view all the answers

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