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

Learn TensorFlow 2.0 = implement mac...

Singh, Pramod.

Linked to FindBook

Google Book

Amazon

博客來

Learn TensorFlow 2.0 = implement machine learning and deep learning models with Python /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Learn TensorFlow 2.0/ by Pramod Singh, Avinash Manure.
Reminder of title:	implement machine learning and deep learning models with Python /
Author:	Singh, Pramod.
other author:	Manure, Avinash.
Published:	Berkeley, CA :Apress : : 2020.,
Description:	xvi, 164 p. :ill., digital ;24 cm.
[NT 15003449]:	Chapter 1: Introduction to TensorFlow 2.0 -- Chapter 2: Supervised Learning with TensorFlow 2.0 -- Chapter 3: Neural Networks and Deep Learning with TensorFlow 2.0 -- Chapter 4: Images with TensorFlow 2.0 -- Chapter 5: NLP Modeling with TensorFlow 2.0 -- Chapter 6: TensorFlow Models in Production.
Contained By:	Springer eBooks
Subject:	Machine learning. -
Online resource:	https://doi.org/10.1007/978-1-4842-5558-2
ISBN:	9781484255582

Learn TensorFlow 2.0 = implement machine learning and deep learning models with Python /
Singh, Pramod.

Learn TensorFlow 2.0implement machine learning and deep learning models with Python /[electronic resource] :by Pramod Singh, Avinash Manure. - Berkeley, CA :Apress :2020. - xvi, 164 p. :ill., digital ;24 cm.

Chapter 1: Introduction to TensorFlow 2.0 -- Chapter 2: Supervised Learning with TensorFlow 2.0 -- Chapter 3: Neural Networks and Deep Learning with TensorFlow 2.0 -- Chapter 4: Images with TensorFlow 2.0 -- Chapter 5: NLP Modeling with TensorFlow 2.0 -- Chapter 6: TensorFlow Models in Production.

Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with introducing TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using TensorFlow 2.0. It also demonstrates how to build models using customer estimators. Further, it explains how to use TensorFlow 2.0 API to build machine learning and deep learning models for image classification using the standard as well as custom parameters. You'll review sequence predictions, saving, serving, deploying, and standardized datasets, and then deploy these models to production. All the code presented in the book will be available in the form of executable scripts at Github which allows you to try out the examples and extend them in interesting ways. You will: Review the new features of TensorFlow 2.0 Use TensorFlow 2.0 to build machine learning and deep learning models Perform sequence predictions using TensorFlow 2.0 Deploy TensorFlow 2.0 models with practical examples.

ISBN: 9781484255582

Standard No.: 10.1007/978-1-4842-5558-2doiSubjects--Uniform Titles:

TensorFlow.
Subjects--Topical Terms:

533906
Machine learning.

LC Class. No.: Q325.5 / .S564 2020

Dewey Class. No.: 006.31

Learn TensorFlow 2.0 = implement machine learning and deep learning models with Python /
LDR:02406nmm a2200325 a 4500 001 2215344
003 DE-He213
005 20200602105024.0
006 m d
007 cr nn 008maaau
008 201119s2020 cau s 0 eng d
020 $a 9781484255582 $q (electronic bk.)
020 $a 9781484255605 $q (paper)
024 7 $a 10.1007/978-1-4842-5558-2 $2 doi
035 $a 978-1-4842-5558-2
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5 $b .S564 2020
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 .S617 2020
100 1 $a Singh, Pramod. $3 3384003
245 1 0 $a Learn TensorFlow 2.0 $h [electronic resource] : $b implement machine learning and deep learning models with Python / $c by Pramod Singh, Avinash Manure.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2020.
300 $a xvi, 164 p. : $b ill., digital ; $c 24 cm.
505 0 $a Chapter 1: Introduction to TensorFlow 2.0 -- Chapter 2: Supervised Learning with TensorFlow 2.0 -- Chapter 3: Neural Networks and Deep Learning with TensorFlow 2.0 -- Chapter 4: Images with TensorFlow 2.0 -- Chapter 5: NLP Modeling with TensorFlow 2.0 -- Chapter 6: TensorFlow Models in Production.
520 $a Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with introducing TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using TensorFlow 2.0. It also demonstrates how to build models using customer estimators. Further, it explains how to use TensorFlow 2.0 API to build machine learning and deep learning models for image classification using the standard as well as custom parameters. You'll review sequence predictions, saving, serving, deploying, and standardized datasets, and then deploy these models to production. All the code presented in the book will be available in the form of executable scripts at Github which allows you to try out the examples and extend them in interesting ways. You will: Review the new features of TensorFlow 2.0 Use TensorFlow 2.0 to build machine learning and deep learning models Perform sequence predictions using TensorFlow 2.0 Deploy TensorFlow 2.0 models with practical examples.
630 0 0 $a TensorFlow. $3 3446650
650 0 $a Machine learning. $3 533906
650 1 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Python. $3 3201289
650 2 4 $a Open Source. $3 2210577
700 1 $a Manure, Avinash. $3 3446649
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-1-4842-5558-2
950 $a Professional and Applied Computing (Springer-12059)