10 Questions
What is the value of the step size after 3 iterations of gradient descent?
0.15753
What is the value of the model parameter a after 5 iterations of gradient descent?
1.26829
What is the purpose of the gradient descent algorithm in this example?
To find the minimum 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?
-67218.0000
What is the value of the model parameter a after 10 iterations of gradient descent?
1.30201
What is the formula for updating the model parameter a in the gradient descent algorithm?
a = a - (step size) * (∂J/∂a)
What is the initial estimate of the model parameter a?
0
What is the value of the step size after 10 iterations of gradient descent?
0.00098
What is the purpose of the calculations in Table 3.2?
To test the understanding of the gradient descent algorithm
What is the graphical representation of the gradient descent algorithm shown in Figure 3.9?
Red arrows indicate change in parameter value a at each iteration
Learn about the fundamentals of supervised machine learning, including how it learns from datasets and makes predictions. Understand the concepts of measurements, labels, and relationships in supervised learning.
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