Reader small image

You're reading from  Deep Learning with Keras

Product typeBook
Published inApr 2017
Reading LevelIntermediate
PublisherPackt
ISBN-139781787128422
Edition1st Edition
Languages
Right arrow
Authors (2):
Antonio Gulli
Antonio Gulli
author image
Antonio Gulli

Antonio Gulli has a passion for establishing and managing global technological talent for innovation and execution. His core expertise is in cloud computing, deep learning, and search engines. Currently, Antonio works for Google in the Cloud Office of the CTO in Zurich, working on Search, Cloud Infra, Sovereignty, and Conversational AI.
Read more about Antonio Gulli

Sujit Pal
Sujit Pal
author image
Sujit Pal

Sujit Pal is a Technology Research Director at Elsevier Labs, an advanced technology group within the Reed-Elsevier Group of companies. His interests include semantic search, natural language processing, machine learning, and deep learning. At Elsevier, he has worked on several initiatives involving search quality measurement and improvement, image classification and duplicate detection, and annotation and ontology development for medical and scientific corpora.
Read more about Sujit Pal

View More author details
Right arrow

Installing Keras on Docker


One of the easiest ways to get started with TensorFlow and Keras is running in a Docker container. A convenient solution is to use a predefined Docker image for deep learning created by the community that contains all the popular DL frameworks (TensorFlow, Theano, Torch, Caffe, and so on). Refer to the GitHub repository at https://github.com/saiprashanths/dl-docker for the code files. Assuming that you already have Docker up and running (for more information, refer to https://www.docker.com/products/overview), installing it is pretty simple and is shown as follows:

The following screenshot, says something like, after getting the image from Git, we build the Docker image:

In this screenshot, we see how to run it:

From within the container, it is possible to activate support for Jupyter Notebooks (for more information, refer to http://jupyter.org/):

Access it directly from the host machine on port:

It is also possible to access TensorBoard (for more information, refer...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Deep Learning with Keras
Published in: Apr 2017Publisher: PacktISBN-13: 9781787128422

Authors (2)

author image
Antonio Gulli

Antonio Gulli has a passion for establishing and managing global technological talent for innovation and execution. His core expertise is in cloud computing, deep learning, and search engines. Currently, Antonio works for Google in the Cloud Office of the CTO in Zurich, working on Search, Cloud Infra, Sovereignty, and Conversational AI.
Read more about Antonio Gulli

author image
Sujit Pal

Sujit Pal is a Technology Research Director at Elsevier Labs, an advanced technology group within the Reed-Elsevier Group of companies. His interests include semantic search, natural language processing, machine learning, and deep learning. At Elsevier, he has worked on several initiatives involving search quality measurement and improvement, image classification and duplicate detection, and annotation and ontology development for medical and scientific corpora.
Read more about Sujit Pal