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Deep Learning For Hydrometeorology And Environmental Science
idioma: inglês
Editor:
Springer Nature Switzerland AG, Janeiro de 2021 ‧
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148,70€
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SINOPSE
This book provides a step-by-step methodology and derivation of deep learning algorithms as Long Short-Term Memory (LSTM) and Convolution Neural Network (CNN), especially for estimating parameters, with back-propagation as well as examples with real datasets of hydrometeorology (e.g.
DETALHES
| Propriedade | Descrição |
|---|---|
| ISBN: | 9783030647766 |
| Editor: | Springer Nature Switzerland AG |
| Data de Lançamento: | Janeiro de 2021 |
| Idioma: | Inglês |
| Dimensões: | 155 x 235 x 20 mm |
| Encadernação: | Capa dura |
| Páginas: | 204 |
| Tipo de produto: | Livro |
| Coleção: | Water Science And Technology Library |
| Classificação Temática: |
Livros em Inglês
>
Ciências Exatas e Naturais
>
Matemática
|
| EAN: | 9783030647766 |
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