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Why might a machine learning system fail where a rule-based system succeeds?

hard🧠 Conceptual Q10 of 15
AI for Everyone - What is Artificial Intelligence
Why might a machine learning system fail where a rule-based system succeeds?
AMachine learning always outperforms rule-based systems
BMachine learning needs sufficient quality data; rule-based works with expert knowledge
CRule-based systems cannot handle any new data
DMachine learning systems never require tuning
Step-by-Step Solution
Solution:
  1. Step 1: Understand machine learning data dependency

    Machine learning requires enough good data to learn patterns well.
  2. Step 2: Understand rule-based system advantage

    Rule-based systems can work well with expert knowledge even if data is scarce.
  3. Final Answer:

    Machine learning needs sufficient quality data; rule-based works with expert knowledge -> Option B
  4. Quick Check:

    Data quality affects ML success [OK]
Quick Trick: ML needs good data; rules need expert knowledge [OK]
Common Mistakes:
MISTAKES
  • Assuming ML always better
  • Ignoring data requirements for ML

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