Launch Stack on AWS (Costs Money!)
Picked 1 Manager Node (t2.micro), Picked 1 Worker Node (t2.medium or t2.large)
- Or 1 Manager Node(t2.medium or t2.large), 0 Worker Nodes(doesn’t matter)
Or CloudFormation->Stacks->Docker->Outputs->Managers
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Click on link under “Managers->Value” and see Public DNS of Manager Node
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Either use “Connect” in EC2 or
ssh -i “mykey.pem” docker@
Make sure mykey.pem has correct permissions
- chmod 400 mykey.pem
**docker service create --name dsnb -p 8888:8888 jupyter/datascience-notebook**
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github link, dockerhub link
-
took about 20 minutes to start up �
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docker service inspect dsnb
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**docker service ps dsnb**
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CloudFormation->Stacks->Docker->Outputs->DefaultDNSTarget for web address
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**jupyter notebook list**
Open
-
Use 8888 for
in this example -
!git clone https://github.com/TrackDR/Geospatial-Jupyter-Notebooks
!git clone https://github.com/rajathkumarmp/Python-Lectures
- Python-Lectures/01.ipynb to start, rest are good too
Docs
- Deploy your app
Other Jupyter/Ipython Github Repositories to clone
-
!git clone https://github.com/TrackDR/ModdedIpythonNotebooks
-
!git clone https://github.com/JWarmenhoven/ISLR-python
!git clone https://github.com/jdwittenauer/ipython-notebooks
-
notebooks/ipython-notebooks/notebooks/language/Intro.ipynb to start
-
skimage-tutorials/lectures/00_images_are_arrays.ipynb
-
docs
Docker images to run
Jupyter
- jupyter/datascience-notebook
Docker images that will need to modify to run here, but looking to the future
Kaggle
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kaggle/python
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kaggle/rstats
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docker service create –name quantlib -p 8888:8888 lballabio/quantlib-notebook
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Videos at vimeo, blog w/ex, book
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ipython docker image
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ontouchstart docker image
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Twisted logic docker image
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Torch/iTorch/Ubuntu 14.04 Docker image: docker pull kaixhin/torch
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Torch/iTorch/CUDA 7/Ubuntu 14.04 Docker image: docker pull kaixhin/cuda-torch
Alternatives to Docker for AWS for running Jupyter Notebooks
CoCalc (subscription based)
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Website, Pricing, Wikipedia, Chrome Extension, GitHub
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Or Run your own CoCalc using their Docker image
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