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Take a Journey from Data to AI

Catch IBM Champion Jean-Georges Perrin's Data Friday series. In special episode, Jean-Georges talks about the journey from Data to AI.​​ Other episodes talk about Apache Spark (and his book!), metadata, UI, schemas, and more. #ibmchampions-featured-library-home #ibmchampions-featured-library...


Blog Entry
Attend a machine learning event and learn how to monetize the data behind your firewall

If you’ve been hearing about machine learning but wondering how it applies to your business, you’ll want to clear your calendar to attend one of three no-cost, face-to-face events in April. Join IBM in Dallas on April 11, Chicago on April 13, or New York on April 18 for a closer look at...

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Blog Entry
Join us in the Apache Spark Maker Event

You're Invited - Apache Spark Maker Community Event On June 6, 2016, leading minds in data and analytics from Tesla, Netflix, Silicon Valley Data Science, and IBM will come together to demonstrate how open data and analytics technologies such as R, Spark, Python and more are forming a...

Armand Ruiz's profile image

Blog Entry
Spark + SPSS Modeler: Boosted Trees, K-Means, and Naive Bayes

We are excited to announce the release of 3 new extensions for SPSS Modeler using MLlib implemented algorithms and PySpark. These three extensions are Gradient-Boosted Trees, K-Means Clustering, and Multinomial Naive Bayes. Niall McCarroll, IBM SPSS Analytic Server Software Engineer, and I ...

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Blog Entry
Announcing IBM SPSS Modeler 18

Today we are releasing Modeler version 18. There a quite a number of important changes and improvements in this version. We have four groupings of changes – Big Data Algorithms in Modeler, changes that continue Extend and Embrace the Value of Open Source, Platform Flexibility and other changes...

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Blog Entry
Coding a Python/Spark Modeler Extension for Collaborative Filtering

Introduction IBM SPSS Modeler 17.1 introduces the ability to build extension nodes written in the Python2 language and leveraging Apache Spark via the Python for Spark (pyspark) API . This feature is introduced in an earlier post . To run extension nodes built in python, Modeler needs...

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Blog Entry
SPSS Extends Spark Support to Cloudera & MapR

IBM this week released an update to IBM SPSS Analytic Server 2.1 that extends SPSS’ support for Apache Spark to all four leading commercial software distributions based on Apache Hadoop. Analytic Server 2.1.0.1 builds on the Spark integration first released in late September by adding support...

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Blog Entry
Spark integration in SPSS Modeler 17.1

In the new release of IBM SPSS Modeler 17.1 we introduced integration with Apache Spark. In this post I will explain more about this integration and why it is so powerful. Why Should Customers Care about Apache Spark? Complex workloads complete significantly faster in Spark compared Hadoop...

Armand Ruiz's profile image

Blog Entry
New SPSS Big Data Algorithms

Last week we announced the new version of IBM SPSS Modeler 17.1 and Analytic Server 2.1. In this new post I would like to showcase the new algorithms that we included in this new release. Combined with SPSS Analytic Server now we offer some additional distributed algorithms: Random Trees,...

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