Discuss why the decision on how much to invest in dev and test set development relies on judgment rather than a strict formula.
Question: In the context of structuring machine learning projects, explain why there is no single rule for how much time and resources to spend creating dev and test sets. What factors might influence a team's judgment?
Sample answer: The investment in dev and test sets relies on judgment because every machine learning project has unique goals, constraints, and data availability. A rigid formula cannot account for varying project scopes; for example, a high-stakes application might demand an exhaustive test set, while a small internal prototype might require far less. Teams must weigh the cost of data collection against the need for accurate performance evaluation to ensure the sets adequately reflect future data.
Key points:
- No strict formula exists for dev/test set investment.
- Depends heavily on specific project context, resources, and goals.
- Requires balancing resource expenditure against the need for reliable evaluation.
Rubric: The essay should explain the lack of a universal rule, cite varying project requirements (like scope or application criticality), and note the trade-off between resource cost and evaluation accuracy.
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Machine Learning
Deep Learning
Machine Learning Strategy
Supervised Learning
Dive into Deep Learning @ D2L
Data Science
Machine Learning Yearning @ DeepLearning.AI
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