aws-samples / Aws Ai Bootcamp Labs
Licence: apache-2.0
This library holds a collection of Notebooks and code examples for AWS AI Bootcamps.
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AWS-AI-Bootcamp-Labs
This library has a collection of Notebooks and code examples for AWS AI Bootcamps.
Content
Amazon Rekognition Demo Notebook
Amazon Comprehend Demo Notebook
Amazon Machine Learning Demo Notebook
Serverless Predictions at Scale
Launch EC2 instance using the deep learning AMI and open fashion MNIST MXNet demo
- 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 [email protected]
- Windows:
- Follow the instructions here to download PuTTY and to convert your private key
- Host Name:
[email protected] - 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.outto 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
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