When to Use Deep Learning

Nga Than
1 min readJan 4, 2022

Most tasks that consist of mapping an input vector to an output vector, and that are easy for a person to do rapidly, can be accomplished via deep learning, given sufficiently large models and sufficiently large datasets of labeled training examples. Other tasks that cannot be described as associating one vector to another, or that are difficult enough that a person would require time to think and reflect in order to accomplish the task, remain beyond the scope of deep learning for now — Goodfellow et al 2016

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Nga Than

Doctoral candidate in sociology @GC_CUNY, passionate about computational social science, digital sociology, tech & developing countries