
DL quiz

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Hard
Asst.Prof.,CSE Chennai
Used 5+ times
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5 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is gradient descent?
a way to determine how well the machine learning model has performed given the different values of each parameter
method to increase the speed of Neural Network operation
an optimization algorithm used to find the values of parameters (coefficients) of a function (f) that minimizes a cost function (cost)
different name for activation function
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is optimization in the context of mathematics and engineering?
Finding the absolute maximum value of a function
Solving complex equations
Minimizing the number of variables in a system
Maximizing the randomness of a system
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is NOT a common optimization technique?
Gradient Descent
Genetic Algorithms
Linear Regression
Simulated Annealing
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In optimization, what does the term "local minimum" refer to?
The smallest value of a function in the entire domain
The smallest value of a function in a specific region of the domain
The largest value of a function in the entire domain
The largest value of a function in a specific region of the domain
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the main advantage of Stochastic Gradient Descent (SGD) compared to traditional Gradient Descent?
SGD always converges to the global minimum
SGD uses the entire dataset in each iteration
SGD is more computationally efficient for large datasets.
SGD guarantees a more accurate convergence
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