Project Planning & Execution Flashcards
7 cards from real AML practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Project Planning & Execution flashcards as text
Which risk is MOST associated with skipping a formal problem framing document before starting ML development?
Answer: Misalignment between the business objective and the ML task formulation, leading to a technically correct but business-irrelevant model
Without formal problem framing, teams often optimize a proxy metric that doesn't map to the true business goal, producing a model that performs well on paper but delivers no value.
What is the purpose of a 'model card' in ML project execution?
Answer: A structured document describing a model's intended use, performance across subgroups, limitations, and ethical considerations
Model cards are standardized documentation artifacts that communicate a model's capabilities, limitations, and responsible use guidelines to downstream stakeholders.
During ML project planning, 'technical debt' most commonly accumulates when:
Answer: Shortcuts like hard-coded thresholds, undocumented preprocessing steps, and monolithic notebooks are used to hit short-term deadlines
Hard-coded values, undocumented transformations, and notebook-first development create fragile, untestable systems that are costly to maintain and extend.
A company wants to deploy an ML model under a strict regulatory compliance requirement. Which planning step is UNIQUELY critical compared to a non-regulated deployment?
Answer: Documenting model lineage, maintaining audit trails, and planning for explainability requirements before development begins
Regulated environments require audit trails, explainability artifacts, and lineage documentation that must be architected into the system from the start, not added retroactively.
When planning compute resources for distributed ML training, what is 'communication overhead' and why does it matter?
Answer: The time gradient synchronization across workers takes, which can dominate wall-clock training time when the model-to-data ratio is high
In distributed training, gradient synchronization overhead can exceed compute time per step, especially for large models on slow interconnects, making network topology a critical planning factor.
A team discovers mid-project that the feature engineering pipeline takes 6 hours to run. What is the BEST project execution response?
Answer: Profile the pipeline, identify bottlenecks, and invest in parallelization or caching to reduce iteration cycle time
Long iteration cycles compound across dozens of experiments; profiling and optimizing the pipeline directly reduces total project duration and increases experimentation throughput.
Which stakeholder communication practice BEST reduces scope creep in ML projects?
Answer: Establishing a formal change request process with documented impact assessment before accepting new requirements
A formal change request process ensures that new requirements are evaluated for feasibility, cost, and timeline impact before being accepted, preventing uncontrolled scope expansion.