Deep learning with R for beginners: design neural network models in R 3.5 using TensorFlow, Keras, and MXNet
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| Main Authors: | , , , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Birmingham
Packt
May 2019
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| Subjects: | |
| Online Access: | Klappentext |
| Physical Description: | vi, 599 Seiten Illustrationen |
| ISBN: | 9781838642709 |
Staff View
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Record in the Search Index
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Deep learning finds practical applications in several domains, while R is the preferred language for designing and deploying deep learning models. This Learning Path introduces you to the basics of deep learning and even teaches you to build a neural network model from scratch. As you make your way through the chapters, you'll explore deep learning libraries and understand how to create deep learning models for a variety of challenges, right from anomaly detection to recommendation systems. The book will then help you cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale deep learning in the cloud, in addition to model optimization, overfitting, and data augmentation. Through real-world projects, you'll also get up to speed with training convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory networks (LSTMs) in R. By the end of this Learning Path, you'll be well versed with deep learning and have the skills you need to implement a number of deep learning concepts in your research work or projects |
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| indexdate | 2025-02-02T19:00:10Z |
| institution | BVB |
| isbn | 9781838642709 |
| language | English |
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| physical | vi, 599 Seiten Illustrationen |
| publishDate | 2019 |
| publishDateSearch | 2019 |
| publishDateSort | 2019 |
| publisher | Packt |
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| spelling | Hodnett, Mark Verfasser (DE-588)1216362572 aut Deep learning with R for beginners design neural network models in R 3.5 using TensorFlow, Keras, and MXNet Mark Hodnett, Joshua F. Wiley, Yuxi (Hayden) Liu, Pablo Maldonado Birmingham Packt May 2019 vi, 599 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier R Programm (DE-588)4705956-4 gnd rswk-swf R Programm (DE-588)4705956-4 s DE-604 Wiley, Joshua F. Verfasser (DE-588)108213497X aut Liu, Yuxi Verfasser (DE-588)1144655390 aut Maldonado, Pablo Verfasser aut Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031329816&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Hodnett, Mark Wiley, Joshua F. Liu, Yuxi Maldonado, Pablo Deep learning with R for beginners design neural network models in R 3.5 using TensorFlow, Keras, and MXNet R Programm (DE-588)4705956-4 gnd |
| subject_GND | (DE-588)4705956-4 |
| title | Deep learning with R for beginners design neural network models in R 3.5 using TensorFlow, Keras, and MXNet |
| title_auth | Deep learning with R for beginners design neural network models in R 3.5 using TensorFlow, Keras, and MXNet |
| title_exact_search | Deep learning with R for beginners design neural network models in R 3.5 using TensorFlow, Keras, and MXNet |
| title_full | Deep learning with R for beginners design neural network models in R 3.5 using TensorFlow, Keras, and MXNet Mark Hodnett, Joshua F. Wiley, Yuxi (Hayden) Liu, Pablo Maldonado |
| title_fullStr | Deep learning with R for beginners design neural network models in R 3.5 using TensorFlow, Keras, and MXNet Mark Hodnett, Joshua F. Wiley, Yuxi (Hayden) Liu, Pablo Maldonado |
| title_full_unstemmed | Deep learning with R for beginners design neural network models in R 3.5 using TensorFlow, Keras, and MXNet Mark Hodnett, Joshua F. Wiley, Yuxi (Hayden) Liu, Pablo Maldonado |
| title_short | Deep learning with R for beginners |
| title_sort | deep learning with r for beginners design neural network models in r 3 5 using tensorflow keras and mxnet |
| title_sub | design neural network models in R 3.5 using TensorFlow, Keras, and MXNet |
| topic | R Programm (DE-588)4705956-4 gnd |
| topic_facet | R Programm |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031329816&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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