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Hands-on deep learning for images with TensorFlow : build intelligent computer vision applications using TensorFlow and Keras

Hands-on deep learning for images with TensorFlow : build intelligent computer vision applications using TensorFlow and Keras (1회 대출)

자료유형
단행본
개인저자
Ballard, Will.
서명 / 저자사항
Hands-on deep learning for images with TensorFlow : build intelligent computer vision applications using TensorFlow and Keras / Will Ballard.
발행사항
Birmingham, UK :   Packt Publishing,   c2018.  
형태사항
88 p. : ill. ; 24 cm.
기타형태 저록
Online version:   Ballard, Will.   Hands-on deep learning for images with TensorFlow   1789532515   (211009) 000045985018  
ISBN
9781789532517
일반주기
Includes index.  
일반주제명
Machine learning. Computer vision. Artificial intelligence. Image processing.
000 00000nam u2200205 a 4500
001 000045982030
005 20190530165220
008 190426s2018 enka 001 0 eng d
020 ▼a 9781789532517
040 ▼a 211009 ▼c 211009 ▼d 211009
082 0 4 ▼a 006.31 ▼2 23
084 ▼a 006.31 ▼2 DDCK
090 ▼a 006.31 ▼b B189h
100 1 ▼a Ballard, Will.
245 1 0 ▼a Hands-on deep learning for images with TensorFlow : ▼b build intelligent computer vision applications using TensorFlow and Keras / ▼c Will Ballard.
260 ▼a Birmingham, UK : ▼b Packt Publishing, ▼c c2018.
300 ▼a 88 p. : ▼b ill. ; ▼c 24 cm.
500 ▼a Includes index.
650 0 ▼a Machine learning.
650 0 ▼a Computer vision.
650 0 ▼a Artificial intelligence.
650 0 ▼a Image processing.
776 0 8 ▼i Online version: ▼a Ballard, Will. ▼t Hands-on deep learning for images with TensorFlow ▼z 1789532515 ▼w (211009) 000045985018
945 ▼a KLPA

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 중앙도서관/서고6층/ 청구기호 006.31 B189h 등록번호 111808605 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

목차

Cover -- Title Page -- Copyright and Credits -- Packt Upsell -- Contributors -- Table of Contents -- Preface -- Chapter 1: Machine Learning Toolkit -- Installing Docker -- The machine learning Docker file -- Sharing data -- Machine learning REST service -- Summary -- Chapter 2: Image Data -- MNIST digits -- Tensors – multidimensional arrays -- Turning images into tensors -- Turning categories into tensors -- Summary -- Chapter 3: Classical Neural Network -- Comparison between classical dense neural networks -- Activation and nonlinearity -- Softmax -- Training and testing data -- Dropout and Flatten -- Solvers -- Hyperparameters -- Grid searches -- Summary -- Chapter 4: A Convolutional Neural Network -- Convolutions -- Pooling -- Building a convolutional neural network -- Deep neural network -- Summary -- Chapter 5: An Image Classification Server -- REST API definition -- Trained models in Docker containers -- Making predictions -- Summary -- Other Books You May Enjoy -- Index -- .

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