IMPORTANT NOTE: Watson machine learning and Openscale have released newer versions of SDKs available for general use. Current available samples use old SDKs and will be obsolate and removed in next couple months. Please use new SDKs going forward(WML and Openscale) to build new models and monitor using Openscale.

For samples using latest SDKs and runtimes, please go to following location:

https://github.com/IBM/watson-openscale-samples

IBM Watson OpenScale tutorials.

IBM Cloud

Tutorial 1. Working with Watson Machine Learning engine

• Step 1: Credit risk prediction model creation, deployment as web-service and monitoring using Watson OpenScale - notebook

Tutorial 2. Working with Custom Machine Learning engine

• Step 1: Creation of Custom Machine Learning engine using Kubernetes cluster - deployment instruction
• Step 2: Data mart creation, model deployment monitoring and data analysis - notebook

Tutorial 3. Working with Azure Machine Learning Studio engine

• Step 1: Data mart creation, model deployment monitoring and data analysis - notebook

Tutorial 4. Working with Amazon SageMaker Machine Learning engine

• Step 1: Creation and deployment of credit risk prediction model - notebook
• Step 2: Data mart creation, model deployment monitoring and data analysis - notebook

Tutorial 5. Working with Azure Machine Learning Service engine

• Step 1: Data mart creation, model deployment monitoring and data analysis - notebook

IBM Cloud Pak for Data

Tutorial 5. Working with IBM SPSS C&DS engine

• Step 1: Data mart creation, model deployment monitoring and data analysis - notebook

Tutorial 6. Working with Watson Machine Learning engine on CP4D

• Step 1: Credit risk prediction model creation, deployment as web-service and monitoring using Watson OpenScale - notebook

Tutorial 7. Generating an explanation for an image-based model on Cloud Pak for Data v. 2.5.0

• Step 1: - Watson OpenScale Explanation for Image Multiclass Classification Model CP4D - notebook

Microsoft Azure Cloud

Tutorial 8. Working with not directly supported engine through Custom ML Engine

• Step 1: Credit risk model (scikit-learn) deployment on Azure ML Service - notebook
• Step 2: Creation of Custom Machine Learning engine and deployment on Azure Cloud as flask application - deployment instruction
• Step 3: OpenScale configuration to work with Custom ML Engine - notebook
• Step 4: Creation of scoring endpoint wrapper to automate payload logging on Azure ML Service - notebook

Model Risk Management and Governance Features

Watson OpenScale Model Risk Management

On Cloud

• Tutorial 1. OpenScale Model Risk Governance with OpenPages Integration on IBM Cloud - notebook
• Tutorial 2. OpenScale Model Risk Management on IBM Cloud - notebook

On Cloud Pak for Data

• Tutorial 3. OpenScale Model Risk Governance with OpenPages Integration on Cloud Pack for Data - notebook
• Tutorial 4. OpenScale Model Risk Management on Cloud Pak for Data - notebook

Metrics Mapping

• Tutorial 5. OpenScale MRM metrics mapping - notebook