Marketplace - Sample notebook templates for sellers

README.md

@@ -185,6 +185,12 @@ This example shows you how to package a model-package/algorithm for listing in A
 
 - [Creating Algorithm and Model Package - Listing on AWS Marketplace](aws_marketplace/creating_marketplace_products) provides a detailed walkthrough on how to package a scikit learn algorithm to create SageMaker Algorithm and SageMaker Model Package entities that can be used with the enhanced SageMaker Train/Transform/Hosting/Tuning APIs and listed on AWS Marketplace.
 
+Once you have created an algorithm or a model package to be listed in the AWS Marketplace, the next step is to list it in AWS Marketplace, and provide a sample notebook that customers can use to try your algorithm or model package. 
+
+* [Curate your AWS Marketplace model package listing and sample notebook](aws_marketplace/curating_aws_marketplace_listing_and_sample_notebook/ModelPackage) provides instructions on how to craft a sample notebook to be associated with your listing and how to curate a good AWS Marketplace listing that makes it easy for AWS customers to consume your model package. 
+
+* [Curate your AWS Marketplace algorithm listing and sample notebook](aws_marketplace/curating_aws_marketplace_listing_and_sample_notebook/Algorithm) provides instructions on how to craft a sample notebook to be associated with your listing and how to curate a good AWS Marketplace listing that makes it easy for your customers to consume your algorithm. 
+
 #### Use algorithms and model packages from AWS Marketplace for machine learning.
 
 These examples show you how to use model-packages and algorithms from AWS Marketplace for machine learning.

aws_marketplace/README.md

@@ -12,6 +12,13 @@ This example notebook shows you how to package a model-package/algorithm for lis
 
 - [Creating Algorithm and Model Package - Listing on AWS Marketplace](creating_marketplace_products) provides a detailed walkthrough on how to package a scikit learn algorithm to create SageMaker Algorithm and SageMaker Model Package entities that can be used with the enhanced SageMaker Train/Transform/Hosting/Tuning APIs and listed on AWS Marketplace.
 
+Once you have created an algorithm or a model package to be listed in the AWS Marketplace, the next step is to list it in AWS Marketplace, and provide a sample notebook that users can use to try your algorithm or model package. 
+
+* [Curate your AWS Marketplace algorithm listing and sample notebook](curating_aws_marketplace_listing_and_sample_notebook/Algorithm) provides instructions on how to craft a sample notebook to be associated with your listing and how to curate a good AWS Marketplace listing that makes it easy for your customers to consume your algorithm.
+
+* [Curate your AWS Marketplace algorithm listing and sample notebook](curating_aws_marketplace_listing_and_sample_notebook/Algorithm) provides instructions on how to craft a sample notebook to be associated with your listing and how to curate a good AWS Marketplace listing that makes it easy for your customers to consume your algorithm. 
+
+
 #### Use algorithms and model packages from AWS Marketplace for machine learning.
 
 These examples show you how to use model-packages and algorithms from AWS Marketplace for machine learning.
@@ -37,4 +44,3 @@ These examples show you how to use model-packages and algorithms from AWS Market
   - An [Amazon SageMaker Notebook Instance](http://docs.aws.amazon.com/sagemaker/latest/dg/gs-setup-working-env.html)
   - An [S3 bucket](http://docs.aws.amazon.com/sagemaker/latest/dg/gs-config-permissions.html)
   - [AWS Marketplace Subscription](https://aws.amazon.com/marketplace/help/200799470#topic1) to the algorithm/model you wish to use.
-

aws_marketplace/curating_aws_marketplace_listing_and_sample_notebook/Algorithm/README.md

@@ -0,0 +1,22 @@
+### Curating AWS Marketplace Algorithm listing and Sample notebook
+
+It is important to make it easy for users of different levels of expertise to use your algorithm from AWS Marketplace. To do so, we recommend you to reuse the instructions and code available as part of [Sample_Notebook_template](#Sample_Notebook_template) to create a sample notebook that executes end-to-end seamlessly without expecting any user input except `algo_arn` variable and an AWS Marketplace subscription to your ML algorithm.
+
+For each listing, we recommend you to create a separate custom sample notebook repository as soon as you have published your listing in AWS Marketplace and host it in a separate public code repository. 
+
+To create a custom sample notebook using [Sample_Notebook_template](#Sample_Notebook_template), follow these instructions:
+
+In **title_of_your_product**-Algorithm.ipynb, make following changes:
+1. Rename the **title_of_your_product**-Algorithm.ipynb file to something appropriate. Keep the file extension as ipynb, i.e. a notebook document.
+2. Open the notebook document in Amazon SageMaker or other Jupyter notebook editor, specify an appropriate title, and add overview of the algorithm.
+3. Look for "[Title_of_your_Algorithm](Provide link to your marketplace listing of your product)", and replace it with a link to your marketplace listing.
+4. The sample notebook template has multiple placeholders which you need to update to create a high-quality notebook.
+5. Retain the data/input, data/output folder structure, and provide multiple input/output files to demonstrate your algorithm for different scenarios that demonstrate different features of your ML model.
+6. Ensure that your sample notebook executes without asking user to provide any input except for `algo_arn` and an AWS Marketplace subscription to your model listing.
+7. Ensure that `algo_arn` has a placeholder with a value `<Customer to specify Model package ARN corresponding to their AWS region>`.
+8. Ensure that you have removed all notes provided for you in red color from the sample notebook template. 
+9. Review the table of contents of your notebook and ensure that all links work.
+10. Once ready, host the sample notebook on your public GitHUB/Bitbucket/Gitlab repository and link the repository with your AWS Marketplace listing, under additional resources section. 
+11. Ensure that repository is accessible to public.
+
+

aws_marketplace/curating_aws_marketplace_listing_and_sample_notebook/Algorithm/Sample_Notebook_Template/data/inference/input/batch/README.md

@@ -0,0 +1 @@
+Add files to be used by the batch transform job example in your notebook in this folder

aws_marketplace/curating_aws_marketplace_listing_and_sample_notebook/Algorithm/Sample_Notebook_Template/data/inference/input/real-time/README.md

@@ -0,0 +1 @@
+Add the file used by the real-time inference example in your notebook in this folder

aws_marketplace/curating_aws_marketplace_listing_and_sample_notebook/Algorithm/Sample_Notebook_Template/data/inference/output/batch/README.md

@@ -0,0 +1 @@
+Add output of the batch transform job example from your sample notebook in this folder

aws_marketplace/curating_aws_marketplace_listing_and_sample_notebook/Algorithm/Sample_Notebook_Template/data/inference/output/real-time/README.md

@@ -0,0 +1 @@
+Add output of the real-time inference example from your sample notebook in this folder

aws_marketplace/curating_aws_marketplace_listing_and_sample_notebook/Algorithm/Sample_Notebook_Template/data/test/README.md

@@ -0,0 +1 @@
+Add sample test dataset to be used by your sample notebook in this folder

aws_marketplace/curating_aws_marketplace_listing_and_sample_notebook/Algorithm/Sample_Notebook_Template/data/train/README.md

@@ -0,0 +1 @@
+Add sample training dataset to be used by your sample notebook in this folder