IBM SPSS Modeler provides predictive analytics to help you uncover data patterns, gain predictive accuracy and improve decision making.
How IBM SPSS Modeler can help you:
- Speeds up operational tasks for data scientists.
- Enables data preparation and discovery, predictive analytics, model management, and deployment.
- Supports monetizing data assets through machine learning.
- Facilitates the building and running of predictive models anywhere — on any cloud and on premises.
Why choose IBM SPSS Modeler: Key features
- GUI-based data science and machine learning algorithms.
- Empowers coders, non-coders, and analysts.
- Enterprise-class security and governance.
- Integration with popular machine learning frameworks like Scikit-learn and TensorFlow.
- Powerful graphics engine for compelling data visualizations.
- Supports a wide range of predictive modeling techniques including decision trees, neural networks, regression models, and more.
- Enables the use of R, Python, Spark, and Hadoop for enhanced analytics.
Who should choose IBM SPSS Modeler:
- Data scientists looking to speed up operational tasks.
- Organizations needing data preparation, discovery, and predictive analytics.
- Businesses requiring advanced model management and deployment solutions.
- Enterprises looking for a scalable solution with security and governance.
