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.