Although open source code in Python and R is popular because of its low cost, flexibility, and power, the time required to properly create code and ensure that it is working correctly can be frustrating. Not everyone is a programmer or wants to program! That’s why the announcement by IBM in June about IBM Data Science Experience is such a game-changer!
IBM Data Science Experience is a way for data scientists to collaborate and work on data science programs in the most efficient way possible. What if the collaboration could be extended to the data scientist or analyst who wants to build predictive models without code? Data Science Experience enables data scientists to choose their own preferred way to tackle this problem.
Today in our World of Watson conference we announced what everyone was asking for: integration of IBM SPSS Modeler in the Data Science Experience. This is a huge step forward and shows the direction we are heading: Make Data Science and Machine Learning as simple as possible for everyone. Good things really do come to those who wait!
SPSS provides an intuitive interface that is easy for everyone to learn and use—from business users to data scientists. Uncover valuable insights quickly for rapid time-to-value. Then, deploy your machine learning models into production to create intelligent applications. Ready to see how it works? Watch the following video to see how to bring data in, clean it up, and create a Neural Network all in a matter of seconds.
There are thousands of SPSS Modeler users out there and the best news for them is that they can import and bring their SPSS streams within the Data Science Experience - they will work and render as expected!
We are really excited about this new capability and we are glad to see that our users are also getting excited about it:
Today this capability is still in closed beta, but we will invite users to try it out before we open it to the rest of our users. If you're as excited as we are, join the waitlist: SPSS Modeler in Data Science Experience.