Day1_Week2

When an experienced deep learning engineer works on a new problem, they can usually use insight from previous problems to train a good model on the first try, without needing to iterate multiple times through different models. True/False?

• True

• False

Q.

A demographic dataset with statistics on different cities' population, GDP per capita, economic growth is an example of “unstructured” data because it contains data coming from different sources. True/False?

• True

• False

Which of the following are true

• Decreasing the size of a neural network generally does not hurt an algorithm’s performance, and it may help significantly.

• Increasing the size of a neural network generally does not hurt an algorithm’s performance, and it may help significantly.

What does a neuron compute?

• A neuron computes a function g that scales the input x linearly (Wx + b)

• A neuron computes a linear function (z = Wx + b) followed by an activation function

• A neuron computes the mean of all features before applying the output to an activation function

Suppose img is a (32,32,3) array, representing a 32x32 image with 3 color channels red, green and blue. How do you reshape this into a column vector?

• x = img.reshape((3,32*32))

• x = img.reshape((32*32*3,1))

You are building a binary classifier for recognizing cucumbers (y=1) vs. watermelons (y=0). Which one of these activation functions would you recommend using for the output layer

• ReLU

• Leaky ReLU

• sigmoid

Which ones are "hyperparameters"?

• number of iterations

• bias vectors

Among the following, which ones are "hyperparameters"?

• size of the hidden layer

• activation values

• weight matrices

Which of the following statements is true?

• The deeper layers of a neural network are typically computing more complex features of the input than the earlier layers.

• The earlier layers of a neural network are typically computing more complex features of the input than the deeper layers

If you have 10,000,000 examples, how would you split the train/dev/test set?

• 98% train . 1% dev . 1% test

• 33% train . 33% dev . 33% test