Learn Before
Error Analysis as a Quantitative Basis for Project Investment Decisions
Before committing significant development time to a proposed improvement, error analysis offers a quick way to estimate how much that work would actually improve accuracy, providing a quantitative basis for deciding whether the investment is worthwhile or whether the time would be better spent on other tasks.
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Machine Learning
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Supervised Learning
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Related
Examples Can Belong to Multiple Error Categories
Discovering New Error Categories While Reviewing Examples
Most Helpful Error Categories Are Ones You Have Ideas to Improve
Error Analysis Is an Iterative Process
Error Category Frequency Helps Indicate Which Categories to Focus On
Pursuing Multiple Error Categories in Parallel
Error Analysis Does Not Yield a Rigid Priority Formula
Error Category Fraction as a Ceiling on Possible Error Reduction
Error Analysis as a Quantitative Basis for Project Investment Decisions
Engineer Reluctance to Perform Error Analysis Despite Its Low Time Cost
Mislabeled Examples in the Dev Set
Splitting a Large Dev Set into a Manually Examined Subset and a Hands-Off Subset
Build a Basic System Quickly and Iterate Using Error Analysis
Training Set Error Analysis for High Bias
Manually Reviewing 100 Speech Recognition Dev Set Examples
Debugging Inference Algorithms
Error Analysis by Parts
Error Analysis as Data Science for ML Mistakes
No Single Right Way to Perform Error Analysis
Human-Solvable Problems Enable More Powerful Error Analysis Tools
What does error analysis primarily examine to understand an ML system's mistakes?
There is exactly one correct method for conducting error analysis on an ML system.
The process of looking at misclassified examples to understand error causes is called _____.
Match each error analysis concept to its correct description from Machine Learning Yearning.
Order the steps of conducting a basic error analysis on a dev set as described in Machine Learning Yearning.
What is the primary goal of reviewing misclassified examples during error analysis, even in categories you cannot yet fix?
Machine Learning Yearning describes error analysis as an iterative process.
Error analysis can often help you figure out how _____ different improvement directions are.
Match each error analysis activity to the benefit it provides according to Machine Learning Yearning.
Order the reasoning steps for deciding which error categories to pursue after completing an initial error analysis.
Learn After
What should you do BEFORE investing a month of development time on a proposed ML improvement?
Error analysis provides a quantitative basis for deciding whether to invest development time in a proposed improvement.
Before investing a month on a task, Ng recommends you first _____ how much it will actually improve the system's accuracy.
Match each error analysis concept to its role in making project investment decisions.
Order the steps for using error analysis to make a project investment decision.
What does the 'simple counting procedure' of error analysis give you a quick way to estimate?
According to Machine Learning Yearning, you should implement a proposed improvement before estimating its potential accuracy gain.
Error analysis gives you a quick way to estimate the possible _____ of incorporating an improvement into your ML system.
Match each error analysis result to the investment decision it most directly supports.
Order the reasoning steps for deciding whether a specific error category is worth one month of development time.