Software Engineering › Learn step by step › Y12 Software Automation
Item 325 of 426 · Year 12: Software Automation, 32 of 35
MLOps design stage
Term
Jump to a topic
- Exam format, question types and command words (46)
- Year 11: Programming Fundamentals (69)
- Year 11: The Object-Oriented Paradigm (33)
- Year 11: Programming Mechatronics (29)
- Year 12: Secure Software Architecture (57)
- Year 12: Programming for the Web (59)
- Year 12: Software Automation (35)
- Year 12: The Software Engineering Project (47)
- Diagrams and modelling tools (18)
- Python, SQL, pseudocode and CSS patterns (33)
Definition
Define the business problem, refactor it into a machine learning problem, define success metrics and research the available data.
Example: Success metric: 95% accuracy.
Found in: course specifications, school notes.
Where you'll use it in the test
Syllabus area: Y12 Software Automation.
Question types it can appear in
- Short answer: Define, outline or explain it and tie it to the scenario.
- Multiple choice: Pick the option that matches the definition or example.
- Drag into order: Know where it sits in the sequence.
How to use it
A model sentence
“Define the business problem, refactor it into a machine learning problem, define success metrics and research the available data.” Then apply it: Success metric: 95% accuracy.
In a short answer, give the definition in your own words first, then tie it to the situation in the question. Do not copy the example above unless it fits the scenario.
Command words used with it
No linked question shows the command word for this term. Across the past short answer questions in this bank the words used most are: Explain, Outline, Describe, Compare, Classify, Analyse. Check the actual word in your question.
Go deeper
- Flashcard: MLOps design stage in Software Automation (Year 12) · study that set
- Memorise: AI v ML; ML supporting automation (DevOps, RPA, BPA)
- Full term page: every question, note and marking comment for MLOps design stage
Check yourself
Explain “MLOps design stage” in one sentence, give an example, and name a question type that could test it.
Reveal the answer
Define the business problem, refactor it into a machine learning problem, define success metrics and research the available data.
Example: Success metric: 95% accuracy.
Could be tested as: Short answer, Multiple choice, Drag into order.