One Paragraph of project description goes here
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
Here are instructions to set up TensorFlow dev environment on Docker if you are running Windows, and configure it so that you can access Jupyter Notebook from within the VM + edit files in your text editor of choice on your Windows machine.
First, install https://www.docker.com/docker-toolbox
Since this is Windows, creating the Docker group "docker" is not necessary.
FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.
#!/bin/sh | |
# Set up the Heroku scheduler to run this command every hour. See example setup at https://goo.gl/nMCSH3 | |
# | |
# Requires env vars to be set in Heroku with `heroku config:set`: | |
# - HEROKU_APP_NAME: this is just the app name in Heroku, i.e. `heroku apps` will list all apps you have access to | |
# - HEROKU_CLI_USER: Once Heroku CLI is authenticated (https://goo.gl/Qypr4x), check `cat .netrc` (or `_netrc` on Windows), | |
# look for `login` under `machine api.heroku.com` | |
# - HEROKU_CLI_TOKEN: As above, but use the `password` field | |
# |