Neural Network Basics Quiz

What is the basic architecture of an Artificial Neural Network inspired by?

• Genetic algorithms

• Quantum mechanics

• The neurons in the brain

• Computer processors

What is the most widely used loss function in Neural Networks?

• Mean Squared Error (MSE)

• Root Mean Squared Error (RMSE)

• Mean Absolute Error (MAE)

• Cross Entropy Error

What does the Mean Squared Error measure in a Neural Network?

• The speed of the training process

• The loss of the network

• The complexity of the network

• The accuracy of the predictions

What is the result of finding the mean of the squared errors in the Mean Squared Error?

• The Mean Absolute Error

• The Mean of the squared errors

• The Root Mean Squared Error

• The Mean Squared Error

What is the goal of training a Neural Network in terms of minimizing loss?

• Ignoring the loss

• Maximizing the loss

• Minimizing the loss

• Balancing the loss

What is the measure of the loss of a Neural Network?

• Cross Entropy Error

• Mean Absolute Error

• Mean Squared Error

• Root Mean Squared Error

What is the first step in finding the Mean Squared Error?

• Finding the mean of all individual values

• Finding the mean of the squared errors

• Squaring the differences individually

• Finding the differences between individual predicted outputs and the expected outputs

What is the second step in finding the Mean Squared Error?

• Finding the mean of all individual values

• Finding the mean of the squared errors

• Squaring the differences individually

• Finding the differences between individual predicted outputs and the expected outputs

What is the third step in finding the Mean Squared Error?

• Finding the mean of all individual values

• Finding the mean of the squared errors

• Squaring the differences individually

• Finding the differences between individual predicted outputs and the expected outputs

Given the True values and Predicted values of y, what is the Mean Squared Error?

• The Mean of the squared errors

• The Mean Squared Error

• The Root Mean Squared Error

• The Mean Absolute Error