Hi all,
Here is a suggestion for reducing the barrier to entry for SystemML: "Have a detailed quickstart guide/video using Notebook on free (or trial-based) hosting solution like IBM Bluemix or Data Scientist Workbench". I have create a sample tutorial: https://github.com/niketanpansare/systemml_tutorial Missing items in above tutorial: 1. Create a separate section for Notebook rather than have it hidden under MLContext Programming guide ( http://apache.github.io/incubator-systemml/spark-mlcontext-programming-guide.html ). 2. Add Python Notebooks (This requires attaching both jars and python MLContext to Zeppelin or Jupyter context). 3. Allow users to use jars from our nightly build (see my jupyter example) as well as released version (see my zeppelin example). 4. Tutorials for all our algorithms using real world dataset. Example: https://www.ibm.com/support/knowledgecenter/SSPT3X_2.1.2/com.ibm.swg.im.infosphere.biginsights.tut.doc/doc/tut_Mod_BigR.html . 5. DML Kernel for Zeppelin (see https://issues.apache.org/jira/browse/SYSTEMML-542). 6. Other hosting services such as AzureML. 7. Tutorial that shows SystemML's integration with MLPipeline. These missing items can be broken down into relatively small tasks with detailed specification that external contributors can work on. Any thoughts ? Thanks, Niketan Pansare IBM Almaden Research Center E-mail: npansar At us.ibm.com http://researcher.watson.ibm.com/researcher/view.php?person=us-npansar
