Palpable 发表于 2025-3-23 13:07:07

Debas Senshaw,Hossana Twinomurinziy easily getting started with Tensorflow. Keras allows employing Tensorflow without losing its flexibility and capability. In the following, two applications (i.e., temporal and spatial deep learning) are presented to illustrate how to use Keras with python.

金盘是高原 发表于 2025-3-23 17:34:29

http://reply.papertrans.cn/27/2647/264608/264608_12.png

PAN 发表于 2025-3-23 18:10:14

Updating Weights, to improve the speed of convergence and to find the best trajectory to reach the optimum of the employed loss function for a network. In this chapter, those methods for updating weights are explained.

THROB 发表于 2025-3-24 02:09:49

Tensorflow and Keras Programming for Deep Learning,y easily getting started with Tensorflow. Keras allows employing Tensorflow without losing its flexibility and capability. In the following, two applications (i.e., temporal and spatial deep learning) are presented to illustrate how to use Keras with python.

Pantry 发表于 2025-3-24 03:06:50

0921-092Xtheir applications to hydrometeorological and environmental studies with real hydrological and environmental data. This book covers the major deep learning algorithms as Long Short-Term Memory (LSTM) and Convo978-3-030-64779-7978-3-030-64777-3Series ISSN 0921-092X Series E-ISSN 1872-4663

persistence 发表于 2025-3-24 06:38:46

http://reply.papertrans.cn/27/2647/264608/264608_16.png

bile648 发表于 2025-3-24 11:35:18

Book 2021ence are very rare.. .This book focuses on the explanation of deep learning techniques and their applications to hydrometeorological and environmental studies with real hydrological and environmental data. This book covers the major deep learning algorithms as Long Short-Term Memory (LSTM) and Convo

jocular 发表于 2025-3-24 18:02:47

https://doi.org/10.1007/978-3-319-66387-6esented, including the definition and pros and cons of deep learning, followed by the recent applications of deep learning models in hydrological and environmental fields. The structure of the remaining chapters for this book is also explained.

神刊 发表于 2025-3-24 22:02:10

http://reply.papertrans.cn/27/2647/264608/264608_19.png

orient 发表于 2025-3-25 00:50:52

http://reply.papertrans.cn/27/2647/264608/264608_20.png
页: 1 [2] 3 4 5
查看完整版本: Titlebook: Deep Learning for Hydrometeorology and Environmental Science; Taesam Lee,Vijay P. Singh,Kyung Hwa Cho Book 2021 The Editor(s) (if applicab