** Create amazon AWS account **

** Request EC2 limit upgrade **

• https://aws.amazon.com/contact-us/ec2-request
• Ireland (EU)
• p2.xlarge
• reason: fast.ai MOOC

** Download Anaconda for python 2.7 **

• https://www.continuum.io/downloads

** Install AWS CLI **

• pip install awscli
• check by typing aws. If it complains about locale's check this site

** Create new AWS user **

• https://console.aws.amazon.com/iam/home?region=eu-west-1#/users$new?step=details
• [username]
• Check 'Programmatic access'
• next
• Add policies directly -> 'AdministratorAccess'
• next
• Copy / paste Access key ID & Secret access key somewhere safe (credentials.txt)

Configure AWS

• aws configure
• Enter previous generated credentials
• Region: eu-west-1
• Output: text

Download setup script

• Check the git repo https://github.com/fastai/courses/tree/master/setup
• Download setup file:

wget https://raw.githubusercontent.com/fastai/courses/master/setup/setup_p2.sh

• chmod 775 setup_p2.sh

Run setup

• ./setup_p2.sh
• Copy output in credentials
• Copy connection command

Connect to server

• ssh -i /Users/[localUser]/.ssh/aws-key.pem ubuntu@[instanceUrl]
• When prompted type 'yes'

Update packages & reboot

• Undo bug with history: sudo rm .bash_history
• sudo apt-get update
• sudo apt-get upgrade
• sudo reboot now

Check setup

• After reboot, login again and check nvidia drivers: nvidia-smi
• Trouble shoot http://wiki.fast.ai/index.php/AWS_install

Start notebook

• jupyter notebook
• Goto url: http://[instanceUrl]:8888
• Default pass 'dl_course'

Check notebooks

• Create new notebook in 'nbs' folder usding Python [conda root]
• check basic command (like 1+1)
• check imports import theano & import keras

Shortcuts

• Download aliases wget https://raw.githubusercontent.com/fastai/courses/master/setup/aws-alias.sh
• source aws-alias.sh

Setup notebooks

• Fork the gitrepo https://github.com/fastai/courses

Perhaps rename it to something sensible, like fastai-courses?

• SSH to machine (aws-ssh)
• cd ~ if you are not already there
• Clone your repo git clone https://github.com/[repoUrl]
• Make a link to notebooks ln -s ~/[repoName]/deeplearning1/nbs/ nbs/deeplearning1
• Run jupyter in background jupyter notebook &> /dev/null &
• Make data dir mkdir ~/nbs/data and change to it cd ~/nbs/data
• Download dogs&cats wget http://www.platform.ai/data/dogscats.zip
• Install unzip sudo apt-get install unzip
• Unzip the data unzip -q dogscats.zip
• Go to your notebook http://[instanceUrl]:8888/notebooks/deeplearning1/lesson1.ipynb
• Step through the process of lesson1.ipynb

Kaggle CLI

• Create profile at https://www.kaggle.com/
• On server: pip install kaggle-cli
• kg config -g -u [username] -p [password] -c dogs-vs-cats-redux-kernels-edition
• mkdir ~/nbs/data/dogscats.2 and cd to it
• Go to https://www.kaggle.com/c/dogs-vs-cats-redux-kernels-edition and accept competition requirements (by downloading the data)
• On server: kg download