Sagemaker Fraud Detection Workshop
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
Enter a 12-character "hash" provided to you by workshop organizer.
Click on "Accpet Terms & Login"
![Navigate to Sagemaker Service](https://github.com/images/image-01.png)
![Navigate to Sagemaker Service](https://github.com/images/image-02.png)
Please, log off from any other AWS accounts you are currently logged into
Click on "Open AWS Console"
![Navigate to Sagemaker Service](https://raw.githubusercontent.com/digitalmerekato/amazon-sagemaker-fraud-detection/master/images/image-03.png)
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).
![Navigate to Sagemaker Service](https://github.com/images/image-04.png)
![Navigate to Sagemaker Service](https://github.com/images/image-05.png)
Scroll down past "Create Role" and Click on "TeamRole"
![Navigate to Sagemaker Service](https://github.com/images/image-06.png)
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
![Navigate to Sagemaker Service](https://github.com/images/image-07.png)
Enter "SageMaker" in the search bar and click on it
![Navigate to Sagemaker Service](https://github.com/images/image-08.png)
You should see a screen like this.
Click on the orange button "Create Notebook Instance"
![Navigate to Sagemaker Service](https://github.com/images/image-09.png)
- 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"
![Navigate to Sagemaker Service](https://github.com/images/image-10.png)
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"
![Navigate to Sagemaker Service](https://github.com/images/image-11.png)
In Jupyter Notebook console, please, click on 'New' -> 'Terminal' on the right-hand side
![Navigate to Sagemaker Service](https://github.com/images/image-12.png)
A new Chrome browser tab will open displaying a command prompt terminal
In the terminal tap, please, issue these two commands:
You should see output similar to this:
![Navigate to Sagemaker Service](https://github.com/images/image-13.png)
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
![Navigate to Sagemaker Service](https://github.com/images/image-14.png)
Open SageMaker Console by clicking on "Services" and searching for Sagemaker
![Navigate to Sagemaker Service](https://github.com/images/image-08.png)
This library is licensed under the MIT-0 License. See the LICENSE file.