Getting started with building, deploying, and trusting models
To get started with building, deploying, and trusting models, understand the overall workflow, choose a tutorial, and check out other learning resources for working with Watson Studio in Cloud Pak for Data.
Overview of the model workflow
The model workflow has three main steps: build a model asset, deploy the model, and build trust in the model.
Build a model asset
- Create a project.
- Add data to the project. If necessary, prepare your data.
- Choose a tool to build a model. You can choose from code editors, graphical canvas, or automatic tools.
Deploy the model
- Create a deployment space and add the model to it.
- Deploy and score the model, and review prediction scores and insights.
- Monitor deployment jobs in a dashboard.
Build trust in your models
- Evaluate your deployment for bias or drift.
- Update your data and retrain the model until you reach your quality goals.
- Update deployments with better-performing models.
- Continue to evaluate, retrain, and update the deployed model.
Tutorials
This tutorial provides a description of the tool, a video, the instructions, and additional learning resources:
Tutorial | Description | Expertise for tutorial |
---|---|---|
Build and deploy a machine learning model with AutoAI | Automatically build model candidates with the AutoAI tool. | Build, deploy, and test a model without coding. |
Build and deploy a machine learning model in a notebook | Build a model by updating and running a notebook that uses Python code and the Watson Machine Learning APIs. | Build, deploy, and test a scikit-learn model using Python code. |
Build and deploy a machine learning model with SPSS Modeler | Build a C5.0 model using the SPSS Modeler tool. | Drop data and operation nodes on a canvas and select properties. |
Build and deploy a Decision Optimization model | Automatically build scenarios with the Modeling Assistant. | Solve and explore scenarios, then deploy and test a model without coding. |
Learning resources
Documentation
Videos
- A comprehensive set of videos that show many common machine learing tasks in Cloud Pak for Data.
Training
- Watson Studio Methodology is an IBM Training e-Learning course that provides an in-depth look at Watson Studio.
- Take control of your data with Watson Studio is a learning path that consists of step-by-step tutorials that explain the process of working with data using Watson Studio.
- Build models using Jupyter Notebooks in IBM Watson Studio is a tutorial that explains how to set up, run, and deploy Jupyter Notebooks.