
Data Science and Machine Learning (Theory and Projects) A to Z - DNN and Deep Learning Basics: Automatic Differentiation
Interactive Video
•
Computers
•
11th - 12th Grade
•
Practice Problem
•
Hard
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7 questions
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1.
OPEN ENDED QUESTION
3 mins • 1 pt
What is the loss function described in the text?
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2.
OPEN ENDED QUESTION
3 mins • 1 pt
How do you compute the derivative of the loss function with respect to the parameters A and B?
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3.
OPEN ENDED QUESTION
3 mins • 1 pt
What values are assigned to the parameters A and B in the example?
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4.
OPEN ENDED QUESTION
3 mins • 1 pt
What is the significance of setting 'requires_grad' to true for parameters in Pytorch?
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5.
OPEN ENDED QUESTION
3 mins • 1 pt
What command is used to compute the gradient in Pytorch?
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6.
OPEN ENDED QUESTION
3 mins • 1 pt
What is the output of the gradient with respect to A when A is 2 and B is 4?
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7.
OPEN ENDED QUESTION
3 mins • 1 pt
Explain how automatic differentiation simplifies the process of computing gradients.
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