Neural Networks and Deep Learning

What does the analogy “AI is the new electricity” refer to?

• AI is powering personal devices in our homes and offices, simimlar to electricity

• Through the "smart grid", AI is delivering a new wave of electricity

• AI runs on computers and is thus powered by electricity, but it is letting computers do things not possible before

• Similar to electricity starting about 100 years ago, AI is transforming multiple industries

Answer explanation

AI is transforming many fields from the car industry to agriculture to supply-chain...

Which of these are reasons for Deep Learning recently taking off? (Check the three options that apply.)

• Deep Learning has resulted in significant improvements in important applications such as online advertising, speech recognition, and image recognition

• We have access to a lot more data

• We have access to a lot more computational power

• Neural Networks are a brand new field

Recall this diagram of iterating over different ML ideas. Which of the statements below are true? (Check all that apply.)

• Faster computation can help speed up how long a team takes to iterate to a good idea

• Being able to try out ideas quickly allows deep learning engineers to iterate more quickly

• Recent progress in deep learning algorithms has allowed us to train good models faster (even without changing the CPU/GPU hardware)

• It is faster to train on a big dataset than a small dataset

When experienced deep learning engineers work 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?

• False

• True

Answer explanation

Finding the characteristics of a model is key to having good performance. Although experience can help, it requires multiple iterations to build a good model.

Which one of these plots represents a ReLU activation function?

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Images for cat recognition is an example of “structured” data, because it is represented as a structured array in a computer. True/False?

• True

• False

Which of the following are examples of structured data? Choose all that apply.

• A dataset with zip code, income, and name of a person

• A set of audio recordings of a person saying a single word

• A dataset of weight, height, age, the sugar level in the blood, and arterial pressure

• A dataset with short poems

RNNs (Recurrent Neural Networks) are good for data with a temporal component. True/False?

• False

• True

From the given diagram, we can deduce that Large NN models are always better than traditional learning algorithms. True/False?

• True

• False

Why is an RNN (Recurrent Neural Network) used for machine translation, say translating English to French? (Check all that apply.)

• It is stricly more powerful than a Convolutional Neural Network (CNN)

• It is applicable when the input/output is a sequence (e.g., a sequence of words).

• RNNs represent the recurrent process of Idea->Code->Experiment->Idea->...

• It can be trained as a supervised learning problem