Duration
14 hours (usually 2 days including breaks)
Requirements
- R
- Python
Overview
Apache SystemML is a distributed and declarative machine learning platform.
SystemML provides declarative large-scale machine learning (ML) that aims at flexible specification of ML algorithms and automatic generation of hybrid runtime plans ranging from single node, in-memory computations, to distributed computations on Apache Hadoop and Apache Spark.
Audience
This course is suitable for Machine Learning researchers, developers and engineers seeking to utilize SystemML as a framework for machine learning.
Course Outline
Running SystemML
- Standalone
- Spark MLContext
- Spark Batch
- Hadoop Batch
- JMLC
Tools
- Debugger
- IDE
- Troubleshooting
Languages and ML Algorithms
- DML
- PyDML
- Algorithms