Apache SystemML is a declarative style language designed for large-scale machine learning. It provides automatic generation of optimized runtime plans ranging from single-node, to in-memory, to distributed computations on Apache Hadoop and Apache Spark. SystemML algorithms are expressed in R-like or Python-like syntax that includes linear algebra primitives, statistical functions and ML-specific constructs.
As a data scientist, engineer, or just a fellow interested in machine learning, your productivity will increase while having the flexibility to express custom analytics and not worry about the underlying optimization engine. Automatic scalability and optimization is handled by SystemML. This course will not only provide you with a view of how the optimizers function but also provide hands-on examples of ML algorithms and how to run them.
COURSE SYLLABUS
Module 1 - What is SystemML?
Explain the purpose and the origin of SystemML
List the alternatives to SystemML
Compare performances of SystemML with the alternatives
Module 2 - SystemML and the Spark MLContext
Use MLContext to interact with SystemML (in Scala)
Module 3 - Working with BigSheets
Describe and use a number of SystemML algorithms
Module 4 - Working with BigSheets
Explain the purpose of DML
Describe the DML language
List some of the built-in functions
Module 5 - Working with BigSheets
Describing the optimizer stack
Explaining how SystemML know it's better to run on one machine
Explaining why SystemML is so much faster than single-node R
GENERAL INFORMATION
This course is self-paced.
It can be taken at any time.
It can be audited as many times as you wish.
RECOMMENDED SKILLS PRIOR TO TAKING THIS COURSE
Have taken the Big Data Fundamentals learning path.
Have taken the Hadoop Fundamentals learning path.
Basic understanding of Apache Hadoop and Big Data.
Basic Linux Operating System knowledge.
REQUIREMENTS
None
COURSE STAFF
Henry L. Quach
Henry L. Quach is the Technical Curriculum Developer Lead for Big Data. He has been with IBM for 9 years focusing on education development. Henry likes to dabble in a number of things including being part of the original team that developed and designed the concept for the IBM Open Badges program. He has a Bachelor of Science in Computer Science and a Master of Science in Software Engineering from San Jose State University.
