Semantic Scholar Open Access 2016 2733 sitasi

Neural networks and Deep Learning

B. Efron Trevor J. Hastie

Abstrak

Neural networks (NNs) are a large and complex class of predictors applicable to a variety of tasks, including categorization, regression, and sequence prediction. Typically, NNs are obtained through the combination of simple predictors of the form g(x) = σ ( w⊤x ) . The function σ : R→ R, which is almost always nonlinear, is known as activation function. We focus on feedforward NNs, computing functions of the form f : Rd → Rn. Hence, we do not consider more complex network models, such as recurrent NNs.

Topik & Kata Kunci

Computer Science

Penulis (2)

B. Efron

Trevor J. Hastie

Format Sitasi

APA MLA BibTeX

Efron, B., Hastie, T.J. (2016). Neural networks and Deep Learning. https://doi.org/10.1017/CBO9781316576533.019

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Informasi Jurnal

Tahun Terbit: 2016
Bahasa: en
Total Sitasi: 2733×
Sumber Database: Semantic Scholar
DOI: 10.1017/CBO9781316576533.019
Akses: Open Access ✓