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General Error Attribution Procedure for Multi-Step Pipelines
For a pipeline with steps A, B, and C, test each dev-set mistake by manually replacing A with a perfect output and running the rest of the pipeline. If the system becomes correct, attribute the error to A; otherwise repeat with B, and if that still does not fix the output, attribute the error to C.
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References
Machine Learning Yearning (Deeplearning.ai)
Machine Learning Yearning (Deeplearning.ai)
Machine Learning Yearning (Deeplearning.ai)
Machine Learning Yearning (Deeplearning.ai)
Machine Learning Yearning (Deeplearning.ai)
Machine Learning Yearning (Deeplearning.ai)
Machine Learning Yearning (Deeplearning.ai)
Machine Learning Yearning (Deeplearning.ai)
Machine Learning Yearning (Deeplearning.ai)
Machine Learning Yearning (Deeplearning.ai)
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Machine Learning
Deep Learning
Supervised Learning
Dive into Deep Learning @ D2L
Data Science
Machine Learning Strategy
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General Error Attribution Procedure for Multi-Step Pipelines
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What does error analysis by parts primarily tell you about a machine learning pipeline?
Error analysis by parts can only be performed using a rigorous formal procedure, not informally.
Error analysis by parts tells us what component(s) performance is worth the greatest _____ to improve.
Match each error analysis by parts concept to its correct description from Machine Learning Yearning.
Order the steps of the informal error analysis procedure Ng describes for a self-driving car pipeline.
Which three components make up the self-driving car pipeline Ng uses to illustrate informal error analysis by parts?
The primary goal of error analysis by parts is to help a developer decide which pipeline component to prioritize for improvement.
By carrying out error analysis by parts, you can _____ each mistake the algorithm makes to one or more pipeline components.
Match each component in Ng's self-driving car pipeline to the output it produces.
Order the reasoning steps a developer follows when applying error analysis by parts to prioritize pipeline improvements.
Learn After
Self-Driving Car Error Attribution Scenario
DAG Ordering for Pipeline Error Attribution
What is the purpose of manually replacing a component's output with a 'perfect' output in the error attribution procedure?
If replacing A's output with a perfect output causes the pipeline to produce a correct result, the error should be attributed to component B.
In a pipeline A → B → C, if replacing A's output with a perfect output fixes the system, you attribute the error to _____.
Match each error attribution scenario to the correct conclusion about which pipeline component caused the error.
Order the steps of the general error attribution procedure for a three-step pipeline A → B → C.
In a pipeline A → B → C, under what condition does the error attribution procedure conclude that component C caused the error?
The error attribution procedure requires retraining every pipeline component from scratch for each dev-set mistake analyzed.
The error attribution procedure is applied to each _____ the system makes on the dev set, one at a time.
Match each pipeline component in A → B → C to the diagnostic action taken when testing whether it is the source of a dev-set error.
Order the reasoning steps for deciding which component to prioritize for improvement after running error attribution across many dev-set mistakes.