Data Science Experience is now Watson Studio. Although some images in this code pattern may show the service as Data Science Experience, the steps and processes will still work. In this Code Pattern we will use Apache SystemML running on IBM Watson Studio to perform a Machine Learning exercise. Watson Studio is an interactive, collaborative, cloud-based environment where data scientists, developers, and others interested in data science can use tools (e.g., RStudio, Jupyter Notebooks, Spark, etc.) to collaborate, share, and gather insight from their data. Apache SystemML is a flexible machine learning platform that is optimized to scale with large data sets.

Apache SystemML is now a Top-Level Project (TLP) and supports many different environments. If you are interested to try out new IBM's Watson Machine Learning service - click here With the recent partnership announcement between IBM and Hortonworks, this post describes how to add Apache SystemML to an existing Hortonworks Data Platform (HDP) 2.6.1 cluster for Apache Spark 2.1. Users interested in Python, Scala, Spark, or Zeppelin can run Apache SystemML as described in the corresponding sections. Apache SystemML provides a Python interface that can be installed using pip. See Using VirtualEnv with PySpark - Hortonworks for details on setting up a Python virtual environment.