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Course Outline
Running SystemML
- Standalone
- Spark MLContext
- Spark Batch
- Hadoop Batch
- JMLC
Tools
- Debugger
- IDE
- Troubleshooting
Languages and ML Algorithms
- DML
- PyDML
- Algorithms
Requirements
- R
- Python
14 Hours
Testimonials (5)
The trainer showed that he has a good understanding of the subject.
Marino - EQUS - The University of Queensland
Course - Machine Learning with Python – 2 Days
Keeping it short and simple. Creating intuition and visual models around the concepts (decision tree graph, linear equations, calculating y_pred manually to prove how the model works).
Nicolae - DB Global Technology
Course - Machine Learning
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Department of Jobs, Regions, and Precincts
Course - Artificial Neural Networks, Machine Learning, Deep Thinking
Convolution filter
Francesco Ferrara
Course - Introduction to Machine Learning
The trainer was so knowledgeable and included areas I was interested in.