Learn Before
Engineer Reluctance to Perform Error Analysis Despite Its Low Time Cost
Engineers are often reluctant to perform error analysis because jumping into implementing an idea feels more exciting than questioning whether the idea is worth the time. Skipping error analysis is a common mistake that can leave a team a month in only to discover little benefit, even though manually examining 100 examples takes under two hours at one minute per image and can save that month of wasted effort.
0
1
Tags
Machine Learning
Deep Learning
Supervised Learning
Dive into Deep Learning @ D2L
Data Science
Machine Learning Strategy
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
Why are engineers often reluctant to perform error analysis, according to Andrew Ng?
Manually examining 100 mislabeled examples at one minute per image takes under two hours to complete.
According to Ng, two hours spent on error analysis could save your team up to a _____ of wasted effort.
Match each concept related to error analysis reluctance with its correct description from Andrew Ng's guidance.
Order the steps that illustrate the cost of skipping error analysis, as described by Andrew Ng.
What does Andrew Ng say is a likely consequence of skipping error analysis before implementing an ML improvement?
According to Ng, the feeling that implementing an idea is more exciting than error analysis is rare among ML engineers.
Andrew Ng states that examining _____ examples during error analysis, at one minute each, takes under two hours.
Match each time estimate with what it represents in Andrew Ng's discussion of error analysis cost.
Order the reasoning steps that justify performing error analysis before implementation, as Ng argues.