Sagemaker Fraud Detection Workshop

Lab description

This lab demonstrates three different ML algorithms used for identifying fraudelent transactions on the same dataset:

• SageMaker XGBoost
• AutoEncoders
• Neural Networks

Steps for launching the workshop environment using EVENT ENGINE

Note: these steps were tested on Chrome browser using Mac OS

open a browser and navigate to https://dashboard.eventengine.run/login

Enter a 12-character "hash" provided to you by workshop organizer.

Click on "Accpet Terms & Login"

Click on "AWS Console"

Please, log off from any other AWS accounts you are currently logged into

Click on "Open AWS Console"

You should see a screen like this.

We now need select the correct Identity Role for the workshop

Type "IAM" into the search bar and click on IAM

(Identity and Access Management).

Click on "Roles"

Scroll down past "Create Role" and Click on "TeamRole"

Copy "Role ARN" by selecting the copy icon on the right

You may want to temporariliy paste this role ARN into a notepad

Once you copied TeamRole ARN, click on "Services" in the upper left corner

Enter "SageMaker" in the search bar and click on it

You should see a screen like this.

Click on the orange button "Create Notebook Instance"

On the next webpage,

- Give your notebook a name (no underscores, please)

- Under Notebook instance type, select "ml.c5.2xlarge"

- Under "Permission and encryption" select "Enter a custom IAM role ARN";

- Paste your TeamRole ARN in the cell below labled "Custom IAM role ARN"

Note: your TeamRole ARN will have different AWS account number than what you see here

- Scroll down to the bottom of the page and click on "Create Notebook instance"

You should see your notebook being created. In a couple of minutes, its status will change

from "Pending" to "In Service", at which point, please click on "Open Jupyter"

In Jupyter Notebook console, please, click on 'New' -> 'Terminal' on the right-hand side

A new Chrome browser tab will open displaying a command prompt terminal

In the terminal tap, please, issue these two commands:

$ cd SageMaker

$ git clone https://github.com/aws-samples/amazon-sagemaker-fraud-detection

You should see output similar to this:

You may now close the browser tab with command prompt terminal,

return to Jupyter console and navigate the created folder structure to

amazon-sagemaker-fraud-detection -> notebooks

launch and run each one of the three Jupyter notebooks

Open SageMaker Console by clicking on "Services" and searching for Sagemaker

License

This library is licensed under the MIT-0 License. See the LICENSE file.