DL quiz

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

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

Which of the following is NOT a common optimization technique?

• Gradient Descent

• Genetic Algorithms

• Linear Regression

• Simulated Annealing

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

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