Learn Before
Uncertainty About the Best Machine Learning Strategy Drives Experimentation
For a new machine-learning task, the best approach usually cannot be identified reliably before experiments are run. This uncertainty causes teams, including experienced practitioners, to test and compare multiple candidate approaches before selecting one that performs well enough.
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Uncertainty About the Best Machine Learning Strategy Drives Experimentation
Learn After
Why do ML teams usually test several approaches on a new problem?
The Best ML Approach Is Usually Obvious Before Testing
For a brand-new machine learning task, it is usually _____ to know beforehand which method will work best.
Match Each Situation to the Correct Machine Learning Idea
Order the stages of a typical iterative machine learning workflow when the best solution is not obvious.
How many candidate ideas does an experienced ML practitioner often test before finding a good solution?
Choosing the best ML approach before any experiments is easy for experienced teams and mainly difficult for beginners.
What do teams often test many of before finding a workable machine-learning approach?
Match each development claim to its implication.
Put the reasoning in order for why ML work usually proceeds by iteration.
Why Machine Learning Requires Repeated Experimentation
Choosing an ML strategy for a new prediction task.
Can experts predict the best ML approach in advance?
An Iterative Machine Learning Workflow