The Machine Learning service is a set of REST APIs that you can call from any programming language and that permit the integration of Watson Studio analytics in your applications. Bind your IBM Cloud applications to the Machine Learning service instance and generate the predictive analytics that your applications need to deliver higher value to your users.
Develop applications against Spark, Python, and IBM® SPSS® models that are deployed on a service instance through the powerful REST APIs:
- Retrieve the metadata for a given predictive model
- Deploy models and manage deployed models
- Online deployment (scoring)
- Batch deployment (supporting IBM Cloud IBM Cloud Object Storage and dashDB)
- Stream deployment (supporting IBM Event Streams)
- Retrieve the metadata for a given deployment
- Monitor and retrain deployed models by using the continuous learning system
- Generate predictive analytics by making score requests against deployed models
For more information, see the following examples of REST API use:
- Deploying online models
- Scoring online models
- Deploying batch models
- Deploying stream models
- Continuous learning system
- Using the REST API
Full details about the Machine Learning REST API for Spark and Python models is available from the following Swagger representation.
For more information about the API, see REST API.
For more information about IBM® SPSS® Modeler and the modeling algorithms it provides, see IBM Knowledge Center.