Hands-on deep learning for images with TensorFlow build intelligent computer vision applications using TensorFlow and Keras
Explore TensorFlow's capabilities to perform efficient deep learning on images Key Features Discover image processing for machine vision Build an effective image classification system using the power of CNNs Leverage TensorFlow's capabilities to perform efficient deep learning Book Descrip...
Otros Autores: | |
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Formato: | Libro electrónico |
Idioma: | Inglés |
Publicado: |
Birmingham ; Mumbai :
Packt
2018.
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Edición: | 1st edition |
Materias: | |
Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009630756406719 |
Tabla de Contenidos:
- 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.