What you missed in Big Data: Scaling analytics

The analytics ecosystem grew a little bigger last week with the launch of a new open-source project from IBM Corp. that aims to help simplify the development of machine learning models for data crunching applications. The aptly-named SystemML framework is a product of the company’s work on Watson that abstracts away many of the complicated implementation details involved in building a production-grade algorithm to let analysts focus their energy on creating new features instead.   A user only needs to write their code in their preferred language, whether it’s R or the less specalized Python, and trust SystemML to do the rest. The framework automatically determines the fastest way to execute an algorithm based on the characteristics of the hardware on which it’s running in order to spare data scientists the hassle…


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