This library has a collection of Notebooks and code examples for AWS AI Bootcamps.
Amazon Rekognition Demo Notebook
Amazon Comprehend Demo Notebook
Amazon Machine Learning Demo Notebook
Serverless Predictions at Scale
- Create EC2 IAM role for the workshop as described here. We will apply permission policies as documented in each notebook
- Launch EC2 Instance using the Ubuntu deep learning AMI in eu-west-1, Ireland (p2.xlarge - $0.972/hour) http://amzn.to/2j3FdOZ
- Connect via SSH and tunnel port 8888:
- Linux, Mac:
ssh -i user.pem -L 8888:localhost:8888 ubuntu@ec2-ip-ip-ip-ip.region.compute.amazonaws.com
- Windows:
- Follow the instructions here to download PuTTY and to convert your private key
- Host Name:
ubuntu@ec2-ip-ip-ip-ip.region.compute.amazonaws.com
- Expand Connection and choose Auth, select your .ppk file
- Expand Connection > SSH, choose Tunnels, specify Source Port:
8888
, Destination:localhost:8888
- Choose Add and Open
- Linux, Mac:
- Clone aws-ai-bootcamp-labs github repository
git clone https://github.com/awslabs/aws-ai-bootcamp-labs
- Start jupyter notebook:
nohup jupyter notebook &
tail nohup.out
to get the login token- look for
http://localhost:8888/?token=<your_login_token>
- look for
- Open demo notebook (FashionMNIST_MXNet_Demo.ipynb)
- Select Kernel > Change kernel > Python 2
- Follow steps in notebook