Task Decomposition for ML Experiment

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Decompose ML experiments into structured phases covering setup, implementation, evaluation, and conclusion with task dependencies.

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Decompose this ML experiment into structured tasks.

## Experiment Goal
{{experiment_goal}}

## Hypothesis
{{hypothesis}}

## Available Resources
{{available_resources}}

Apply systematic decomposition:

**Phase 1: Setup**
- Task 1.1: Define success metrics
- Task 1.2: Prepare evaluation datasets
- Task 1.3: Set up experiment tracking
- Task 1.4: Establish baseline

**Phase 2: Implementation**
- Task 2.1: Implement experimental changes
- Task 2.2: Validate implementation correctness
- Task 2.3: Run small-scale tests
- Task 2.4: Debug and iterate

**Phase 3: Evaluation**
- Task 3.1: Run full evaluation
- Task 3.2: Collect metrics
- Task 3.3: Analyze results
- Task 3.4: Statistical significance testing

**Phase 4: Conclusion**
- Task 4.1: Document findings
- Task 4.2: Make recommendation
- Task 4.3: Plan next steps
- Task 4.4: Share learnings

Provide task dependencies and time estimates.

Details

Category

Analysis

Use Cases

Experiment planningML workflowResearch organization

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claude-sonnet-4-20250514gpt-4o
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Task Decomposition for ML Experiment | Promptsy