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Digital Activity Expands the Data Pool for Deep Learning
Widespread use of connected devices and internet-scale applications generates digital records that can be collected into large training datasets. The resulting increase in available training data has contributed to recent deep learning gains.
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Which pair best explains the main forces behind recent deep learning gains?
True or False: Most neural-network ideas were invented only in the last ten years.
Recent progress has been driven by more data and more _____.
Match the main forces behind progress in deep learning to their descriptions.
Arrange the explanation for why deep learning has accelerated recently.
Why long-standing deep learning ideas became effective recently
Explain why two models improve differently as a dataset expands.
Why can expert-crafted features help when labeled data is limited?
Which statement best describes why older deep learning ideas became influential later?
Two major forces behind recent deep learning gains
Digital Activity Expands the Data Pool for Deep Learning
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What most directly explains the growth in data available for deep learning?
Large labeled datasets are identified as one of the major reasons for recent deep learning progress.
Data created through everyday _____ activity can be valuable for training learning systems.
Match each element of the data-growth explanation to its role in advancing deep learning.
Order the data-flow steps from everyday device use to better deep learning models.
Which statement best describes how widespread use of connected devices can accelerate deep learning progress?
Recent deep learning progress has been driven only by more training data.
When digital services produce user interactions at scale, they often generate _____ quantities of data that can be used to train learning systems.
Match each statement in the data-growth argument to the role it plays in the explanation.
Put the argument about data growth in order
Describe how connected-device data has accelerated deep learning.
Why a smartphone app can produce so much training data
How does routine use of connected apps affect training data availability?