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Applied deep learning with TensorFlo...

Michelucci, Umberto.

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Applied deep learning with TensorFlow 2 = learn to implement advanced deep learning techniques with Python /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Applied deep learning with TensorFlow 2/ by Umberto Michelucci.
Reminder of title:	learn to implement advanced deep learning techniques with Python /
Author:	Michelucci, Umberto.
Published:	Berkeley, CA :Apress : : 2022.,
Description:	xxviii, 380 p. :ill., digital ;24 cm.
[NT 15003449]:	Chapter 1 : Optimization and Neural Networks -- Chapter 2: Hands-on with One Single Neuron -- Chapter 3: Feed Forward Neural Networks -- Chapter 4: Regularization -- Chapter 5: Advanced Optimizers -- Chapter 6: Hyperparameter Tuning -- Chapter 7: Convolutional Neural Networks -- Chapter 8: Brief Introduction to Recurrent Neural Networks -- Chapter 9: Autoencoders -- Chapter 10: Metric Analysis -- Chapter 11: General Adversarial Networks (GANs) -- Appendix A: Introduction to Keras -- Appendix B: Customizing Keras.
Contained By:	Springer Nature eBook
Subject:	Python (Computer program language) -
Online resource:	https://doi.org/10.1007/978-1-4842-8020-1
ISBN:	9781484280201

Applied deep learning with TensorFlow 2 = learn to implement advanced deep learning techniques with Python /
Michelucci, Umberto.

Applied deep learning with TensorFlow 2learn to implement advanced deep learning techniques with Python /[electronic resource] :by Umberto Michelucci. - Second edition. - Berkeley, CA :Apress :2022. - xxviii, 380 p. :ill., digital ;24 cm.

Chapter 1 : Optimization and Neural Networks -- Chapter 2: Hands-on with One Single Neuron -- Chapter 3: Feed Forward Neural Networks -- Chapter 4: Regularization -- Chapter 5: Advanced Optimizers -- Chapter 6: Hyperparameter Tuning -- Chapter 7: Convolutional Neural Networks -- Chapter 8: Brief Introduction to Recurrent Neural Networks -- Chapter 9: Autoencoders -- Chapter 10: Metric Analysis -- Chapter 11: General Adversarial Networks (GANs) -- Appendix A: Introduction to Keras -- Appendix B: Customizing Keras.

ISBN: 9781484280201

Standard No.: 10.1007/978-1-4842-8020-1doiSubjects--Topical Terms:

729789
Python (Computer program language)

LC Class. No.: QA76.73.P98 / M53 2022

Dewey Class. No.: 006.31

Applied deep learning with TensorFlow 2 = learn to implement advanced deep learning techniques with Python /
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245 1 0 $a Applied deep learning with TensorFlow 2 $h [electronic resource] : $b learn to implement advanced deep learning techniques with Python / $c by Umberto Michelucci.
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260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2022.
300 $a xxviii, 380 p. : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1 : Optimization and Neural Networks -- Chapter 2: Hands-on with One Single Neuron -- Chapter 3: Feed Forward Neural Networks -- Chapter 4: Regularization -- Chapter 5: Advanced Optimizers -- Chapter 6: Hyperparameter Tuning -- Chapter 7: Convolutional Neural Networks -- Chapter 8: Brief Introduction to Recurrent Neural Networks -- Chapter 9: Autoencoders -- Chapter 10: Metric Analysis -- Chapter 11: General Adversarial Networks (GANs) -- Appendix A: Introduction to Keras -- Appendix B: Customizing Keras.
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