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Deep Learning for Computer Vision

You're reading from   Deep Learning for Computer Vision Expert techniques to train advanced neural networks using TensorFlow and Keras

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788295628
Length 310 pages
Edition 1st Edition
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Author (1):
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Rajalingappaa Shanmugamani Rajalingappaa Shanmugamani
Author Profile Icon Rajalingappaa Shanmugamani
Rajalingappaa Shanmugamani
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Table of Contents (12) Chapters Close

Preface 1. Getting Started 2. Image Classification FREE CHAPTER 3. Image Retrieval 4. Object Detection 5. Semantic Segmentation 6. Similarity Learning 7. Image Captioning 8. Generative Models 9. Video Classification 10. Deployment 11. Other Books You May Enjoy

Deployment in the cloud


The models have to be deployed in the cloud for several applications. We will look at major cloud service providers for this purpose.

AWS

The Amazon Web Services (AWS) extends support to the development and deployment of TensorFlow-based models. Sign up for AWS at https://aws.amazon.com/ and select one of the Amazon Machine Images (AMI). AMIs are images of machines with all the required software installed. You need not worry about installing the packages. AWS provides Deep Learning AMI (DLAMI) for ease of training and deploying deep learning models. There are several options to choose from. Here, we will use Conda as it comes with several packages required for running TensorFlow. There are two options for Python: version 2 and 3. The following code will activate TensorFlow with Keras 2 on Python 3 on CUDA 8:

source activate tensorflow_p36

The following code will activate TensorFlow with Keras 2 on Python 2 on CUDA 8:

source activate tensorflow_p27

Note

You can visit https...

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