東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Deep learning projects using TensorF...

Silaparasetty, Vinita.

Linked to FindBook

Google Book

Amazon

博客來

Deep learning projects using TensorFlow 2 = neural network development with Python and Keras /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep learning projects using TensorFlow 2/ by Vinita Silaparasetty.
Reminder of title:	neural network development with Python and Keras /
Author:	Silaparasetty, Vinita.
Published:	Berkeley, CA :Apress : : 2020.,
Description:	xxv, 421 p. :ill., digital ;24 cm.
[NT 15003449]:	Chapter 1: Getting Started: Installation and Troubleshooting -- Chapter 2: Perceptrons -- Chapter 3: Neural Networks -- Chapter 4: Sentiment Analysist -- Chapter 5: Music Generation -- Chapter 6: Image Colorization -- Chapter 7: Image Deblurring -- Chapter 8: Image Manipulation -- Chapter 9: Neutral Network Collection -- Appendix: Portfolio Tips.
Contained By:	Springer Nature eBook
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-1-4842-5802-6
ISBN:	9781484258026

Deep learning projects using TensorFlow 2 = neural network development with Python and Keras /
Silaparasetty, Vinita.

Deep learning projects using TensorFlow 2neural network development with Python and Keras /[electronic resource] :by Vinita Silaparasetty. - Berkeley, CA :Apress :2020. - xxv, 421 p. :ill., digital ;24 cm.

Chapter 1: Getting Started: Installation and Troubleshooting -- Chapter 2: Perceptrons -- Chapter 3: Neural Networks -- Chapter 4: Sentiment Analysist -- Chapter 5: Music Generation -- Chapter 6: Image Colorization -- Chapter 7: Image Deblurring -- Chapter 8: Image Manipulation -- Chapter 9: Neutral Network Collection -- Appendix: Portfolio Tips.

Work through engaging and practical deep learning projects using TensorFlow 2.0. Using a hands-on approach, the projects in this book will lead new programmers through the basics into developing practical deep learning applications. Deep learning is quickly integrating itself into the technology landscape. Its applications range from applicable data science to deep fakes and so much more. It is crucial for aspiring data scientists or those who want to enter the field of AI to understand deep learning concepts. The best way to learn is by doing. You'll develop a working knowledge of not only TensorFlow, but also related technologies such as Python and Keras. You'll also work with Neural Networks and other deep learning concepts. By the end of the book, you'll have a collection of unique projects that you can add to your GitHub profiles and expand on for professional application. You will: Grasp the basic process of neural networks through projects, such as creating music Restore and colorize black and white images with deep learning processes.

ISBN: 9781484258026

Standard No.: 10.1007/978-1-4842-5802-6doiSubjects--Uniform Titles:

TensorFlow.
Subjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Deep learning projects using TensorFlow 2 = neural network development with Python and Keras /
LDR:02437nmm a2200325 a 4500 001 2222845
003 DE-He213
005 20201130091651.0
006 m d
007 cr nn 008maaau
008 210108s2020 cau s 0 eng d
020 $a 9781484258026 $q (electronic bk.)
020 $a 9781484258019 $q (paper)
024 7 $a 10.1007/978-1-4842-5802-6 $2 doi
035 $a 978-1-4842-5802-6
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .S581 2020
100 1 $a Silaparasetty, Vinita. $3 3461940
245 1 0 $a Deep learning projects using TensorFlow 2 $h [electronic resource] : $b neural network development with Python and Keras / $c by Vinita Silaparasetty.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2020.
300 $a xxv, 421 p. : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1: Getting Started: Installation and Troubleshooting -- Chapter 2: Perceptrons -- Chapter 3: Neural Networks -- Chapter 4: Sentiment Analysist -- Chapter 5: Music Generation -- Chapter 6: Image Colorization -- Chapter 7: Image Deblurring -- Chapter 8: Image Manipulation -- Chapter 9: Neutral Network Collection -- Appendix: Portfolio Tips.
520 $a Work through engaging and practical deep learning projects using TensorFlow 2.0. Using a hands-on approach, the projects in this book will lead new programmers through the basics into developing practical deep learning applications. Deep learning is quickly integrating itself into the technology landscape. Its applications range from applicable data science to deep fakes and so much more. It is crucial for aspiring data scientists or those who want to enter the field of AI to understand deep learning concepts. The best way to learn is by doing. You'll develop a working knowledge of not only TensorFlow, but also related technologies such as Python and Keras. You'll also work with Neural Networks and other deep learning concepts. By the end of the book, you'll have a collection of unique projects that you can add to your GitHub profiles and expand on for professional application. You will: Grasp the basic process of neural networks through projects, such as creating music Restore and colorize black and white images with deep learning processes.
630 0 0 $a TensorFlow. $3 3446650
650 0 $a Machine learning. $3 533906
650 0 $a Neural networks (Computer science) $3 532070
650 1 4 $a Artificial Intelligence. $3 769149
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-1-4842-5802-6
950 $a Professional and Applied Computing (SpringerNature-12059)