If the input to our linear regression object is of 10 dimensions, including the bias, how many variables does our cost or total loss function contain?1 point

How would you create a linear object with ten input features?1 pointmodel=nn.Linear(1,10)model=nn.Linear(10,1)

Suppose your input is a 300*300 color (RGB) image, and you are not using a convolutional network. If the first hidden layer has 100 neurons, each one fully connected to the input, how many parameters does this hidden layer have (assume each neuron has its own bias parameter)?       a.9,000,001b. 27,000,001c.27,000,100d.9,000,100

The loss is a function 1 pointprovides you with a number that lets you know  how good your estimate ismake a prediction

What is learnt in a neural network?1 pointWeights and BiasesOnly weightsOnly biasesNone of the above

What is the purpose of the bias term in a neural network?Review LaterTo provide an additional regularization termTo offset any imbalance in the target variableTo improve the interpretability of the modelTo introduce flexibility in the decision boundary