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Bridge the Gap Between Top Data Science Languages

Altair SLC bridges the gap between the SAS language and open-source languages like Python, R, and SQL. Organizations can now choose and use the languages that will best serve their objectives.

Digital Debunking: Was Data Analytics Able to Predict if Punxsutawney Phil Would See His Shadow?

But before we knew what Phil’s prediction would be, we wondered if we could use Altair RapidMiner to predict whether Phil would see his shadow. Altair RapidMiner’s low-code platform allows users of all skill levels to build machine learning models, and provides hundreds of powerful tools to transform and augment data.

Credit Scoring Series Part Nine: Scorecard Implementation, Deployment, Production, and Monitoring

After a credit scorecard is developed, how can organizations best implement them? Learn all about it in part nine of Altair’s credit scoring series.

Credit Scoring Series Part Eight: Credit Risk Strategies

Part eight of Altair’s credit scoring series is all about credit risk strategy — read on to learn the key ins and outs of credit risk.

Credit Scoring Series Part Seven: Additional Credit Risk Modeling Considerations

Learn about boostrapping, cross-validation, undersampling, and more in part seven of the Altair credit scoring series.

Credit Scoring Series Part Six: Segmentation and Reject Inference

In part six of the Altair credit scoring series, we take a deeper dive into segmentation and reject inference (RI) and how organizations use them to develop credit scorecards.

Credit Scoring Series Part Five: Credit Scorecard Development

How can any organization or team develop an accurate, agile credit scorecard? Find out in part five of the Altair credit scoring series.

Credit Scoring Series Part Four: Variable Selection

What is variable selection in scorecard modeling, and how can you use it to optimize your credit scorecard operations? Learn in Part 4 of the Altair credit scoring series.

Credit Scoring Series Part Three: Data Preparation and Exploratory Data Analysis

With data, it’s “garbage in, garbage out.” Learn how to get the most from your data prep in the latest credit scoring series installment.