/ai-openscale-tutorials

Watson OpenScale tutorials including sample models, notebooks and applications

Primary LanguageJupyter Notebook

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 Private 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 ICP

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

Microsoft Azure Cloud

Tutorial 7. 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