NH_6

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What is the term for labeling pictures of dogs and cats with defining characteristics?

Feature engineering (correct)

Deep learning

Data engineering

Representation learning

In what process are programs written to perform their own feature engineering on raw data?

Data engineering

Deep learning

Feature extraction

Representation learning (correct)

What is the main drawback mentioned when it comes to labeling data for machine learning?

Difficulty in algorithm implementation

Complexity in understanding data

Lack of computing power

Subjectivity in labeling (correct)

Which method allows a machine to automatically discover representations needed for detection or classification?

Deep learning Signup and view all the answers

What type of learning has seen significant advancements within the field based on the provided text?

Deep learning Signup and view all the answers

What distinguishes representation learning from other types of learning discussed in the text?

It performs its own feature engineering on raw data Signup and view all the answers

What is one of the principal challenges for Deep Learning discussed in the text?

The Selectivity/Invariance Problem Signup and view all the answers

Which type of features are coded at each layer of a deep learning network, according to the text?

Complex and simple features Signup and view all the answers

How does deep learning address the selectivity/invariance challenge?

By coding input with increasingly complex features Signup and view all the answers

What is one of the key tasks that deep learning algorithms have made significant advances in, as mentioned in the text?

Handwriting Recognition Signup and view all the answers

In the context of Deep Learning, what does 'invariance' refer to?

Ability to ignore variations in input data Signup and view all the answers

Why is it important for a system to be highly selective in distinguishing between different objects?

To improve generalization and robustness Signup and view all the answers

What distinguishes reinforcement learning from supervised and unsupervised learning?

The network is driven by a reward signal but is not told how to maximize the reward. Signup and view all the answers

How did AlphaGo Zero differ from the original AlphaGo in terms of learning approach?

AlphaGo Zero used reinforcement learning only, while AlphaGo used a mixture of supervised and reinforcement learning. Signup and view all the answers

What is the biological significance of reinforcement learning in animals?

There are parallels between reinforcement learning algorithms and reward processing involving dopamine in the human brain. Signup and view all the answers

What differentiates Go from chess as mentioned in the text?

Go is considered one of the world's most complex games with more possible moves than chess. Signup and view all the answers

How does reinforcement learning differ from simply repeating past successful strategies?

Reinforcement learning requires the network to engage in trial and error for discovering new reward-generating strategies. Signup and view all the answers

What was the outcome of AlphaGo Zero playing against previous versions of AlphaGo?

After 40 days, AlphaGo Zero was able to beat all existing versions of AlphaGo. Signup and view all the answers

What type of input did the machine receive while playing Atari Breakout?

Sensory input similar to what would be seen on the screen during gameplay. Signup and view all the answers

In which type of learning does the network not receive explicit feedback but learns to detect patterns in data?

Unsupervised Learning Signup and view all the answers

What role does dopamine play in reinforcement learning as discussed in the text?

Dopamine drives reward processing within neural networks similar to reinforcement learning algorithms. Signup and view all the answers