Describe how connected-device data has accelerated deep learning.
Question: Write an analytical response explaining why widespread use of connected consumer devices can speed up progress in deep learning.
Sample answer: As more people use smartphones, smartwatches, home assistants, and other connected devices, they generate large volumes of interaction logs, photos, audio clips, and sensor readings. Those datasets provide abundant training material for learning systems. When these data are collected and used to train models, they help improve performance and are one reason deep learning has advanced quickly.
Key points:
- Connected devices are used by many people for many hours.
- Their usage produces large amounts of data.
- The data can be used to train learning algorithms.
- Greater data availability helps drive deep learning progress.
Rubric: Full credit requires identifying connected devices, explaining that their use creates large quantities of data, and stating that this data supports training and improves deep learning.
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Machine Learning
Deep Learning
Supervised Learning
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