Learn Before
Data Availability as a Driver of Deep Learning Progress
Data availability is a major driver of recent deep learning progress because digital-device activity creates large amounts of data that can be fed to learning algorithms.
0
1
Tags
Machine Learning
Deep Learning
Supervised Learning
Dive into Deep Learning @ D2L
Data Science
Machine Learning Strategy
Machine Learning Yearning @ DeepLearning.AI
Related
Data Availability as a Driver of Deep Learning Progress
Computational Scale as a Driver of Deep Learning Progress
Older Learning Algorithms Can Plateau with More Data
Large Neural Networks Benefit from Huge Data
Small Data Regime Can Favor Hand-Engineered Features
According to Andrew Ng, what are the two biggest drivers of recent deep learning progress?
True or False: Neural network ideas are a brand-new invention of the last decade.
Two of the biggest drivers of recent progress have been data availability and _____.
Match each driver of deep learning progress to its correct description.
Order the reasoning steps explaining why deep learning is taking off now.
Explain why decades-old deep learning ideas are only now driving major progress.
Diagnose why a company's old algorithm and new neural network perform differently as data grows.
In one to two sentences, why might a small dataset favor hand-engineered features over a large neural network?
Which statement best reflects the relationship between deep learning ideas and their timing of impact?
True or False: Data availability and computational scale are described as the two biggest drivers of recent deep learning progress.
Learn After
According to Andrew Ng, what is the primary reason data availability has increased to benefit deep learning?
Data availability is listed as one of the two biggest drivers of recent deep learning progress in Machine Learning Yearning.
People spending more time on _____ devices—such as laptops and mobile devices—generates large amounts of data for learning algorithms.
Match each component of the data-availability argument to its role in driving deep learning progress.
Order the steps in the causal chain from digital-device use to deep learning progress as described in Machine Learning Yearning.
Which statement best captures Andrew Ng's view of the link between digital-device usage and deep learning progress?
According to Machine Learning Yearning, data availability is the sole driver of recent deep learning progress.
According to Machine Learning Yearning, digital activities generate _____ amounts of data that can be fed to learning algorithms.
Match each part of Andrew Ng's p. 9 argument to its logical function in the data-availability explanation.
Arrange the steps in the order Andrew Ng uses them to build his argument for data availability as a driver of deep learning progress on p. 9.
Explain the relationship between digital device usage and deep learning progress.
Evaluating the source of data growth for a mobile health application.
How does modern digital device usage directly impact data availability for learning algorithms?