October 19, 2015 By Miran Badzak 2 min read

Predictive Analytics for Bluemix brings machine learning to every developer

Today, we’re announcing the general availability of the Predictive Analytics service on Bluemix.

Predictive Analytics is our machine learning offering that makes it easy for developers and data scientists to work together to integrate predictive capabilities into their applications. Building on the industry standard SPSS analytics platform, Predictive Analytics allows you to develop intelligence-driven applications that make smarter decisions, solve tough problems, and improve the lives of your users.

With Predictive Analytics, you can build sophisticated recommendation engines, analyze and act on user sentiment, provide targeted, more useful advertisements, detect and prevent click fraud, and much more.

With this release, we’re enabling SPSS Modeler users to deploy their models to IBM’s robust, enterprise-class Bluemix platform. Once deployed, application developers can use a well-documented REST API to make scoring requests (predictions) from their Bluemix or standalone applications.

But, we’re just getting warmed up. Soon, we’ll be unleashing the full power of predictive analytics with new features, integrations, and solutions for our developers.

We believe in the power of machine learning. We believe that application code coupled with predictive models enables a new breed of services that help move human/computer interaction forward.

We’re on a mission to bring machine learning to within reach of every developer and data scientist. We want to deliver the best developer experience and the most robust infrastructure so that you, our developers, can be empowered to create the next generation of awesome services.

Today marks the beginning of this journey. Join us.

More from Announcements

Manage the routing of your observability log and event data 

4 min read - Comprehensive environments include many sources of observable data to be aggregated and then analyzed for infrastructure and app performance management. Connecting and aggregating the data sources to observability tools need to be flexible. Some use cases might require all data to be aggregated into one common location while others have narrowed scope. Optimizing where observability data is processed enables businesses to maximize insights while managing to cost, compliance and data residency objectives.  As announced on 29 March 2024, IBM Cloud® released its next-gen observability…

Unify and share data across Netezza and watsonx.data for new generative AI applications

3 min read - In today's data and AI-driven world, organizations are generating vast amounts of data from various sources. The ability to extract value from AI initiatives relies heavily on the availability and quality of an enterprise's underlying data. In order to unlock the full potential of data for AI, organizations must be able to effectively navigate their complex IT landscapes across the hybrid cloud.   At this year’s IBM Think conference in Boston, we announced the new capabilities of IBM watsonx.data, an open…

IBM and SAP unlock business and industry value with new generative AI solutions 

3 min read - IBM Consulting is delivering on our commitment to co-innovate with SAP and collaborate with our clients. As part of our Value Generation Partnership initiative announced earlier this month with SAP, we are releasing the first 10 of 100 planned AI solutions to help clients transform their industries, optimize their business processes and successfully deliver their SAP programs.  Delivering AI business and industry innovation at scale  With the recently announced Value Generation Partnership initiative, IBM and SAP are co-innovating intelligent industry…

IBM Newsletters

Get our newsletters and topic updates that deliver the latest thought leadership and insights on emerging trends.
Subscribe now More newsletters