Front

Why are activation functions important in neural networks?

Back

They add non-linearity to the model

Front

Convolutional neural networks are especially useful for what task?

Back

Image classification

Front

The softmax activation function can be used in the output layer of multi-class classification neural network

Back

True

Front

Which process is used to fit neural networks?

Back

Backpropogation

Front

What popular hidden node activation function assigns an output of 0 to negative inputs?

Back

ReLU

Front

In which of the following scenarios should deep learning be used?
Options:
We have a small sample size,
Maximum accuracy is our only concern,
We need to understand the relationship between input and output,
The relationship between our X and Y is roughly linear

Back

Maximum accuracy is our only concern

Front

When fitting a neural network, we should always interpolate the data if the results are similar to a simpler, non-interpolated model

Back

False

Front

The number of hidden layers in a neural network is the network's _____, and the number of nodes within a hidden layer is the layer's _____.

Back

depth width

Front

Which of the following is not an element of a convolutional neural network? Input layer, Convolution layer, Pooling layers

Back

Descent layer