CT-AI · Question #24
An e-commerce developer built an application for automatic classification of online products in order to allow customers to select products faster. The goal is to provide more relevant products to…
The correct answer is A. Labeling the data correctly. The syllabus explains that supervised learning requires correctly labeled data so the algorithm can learn the relationship between input features and output labels: "In supervised learning, the algorithm creates the ML model from labeled data during the training phase. The…
Question
An e-commerce developer built an application for automatic classification of online products in order to allow customers to select products faster. The goal is to provide more relevant products to the user based on prior purchases. Which of the following factors is necessary for a supervised machine learning algorithm to be successful?
Options
- ALabeling the data correctly
- BMinimizing the amount of time spent training the algorithm
- CSelecting the correct data pipeline for the ML training
- DGrouping similar products together before feeding them into the algorithm
How the community answered
(15 responses)- A73% (11)
- B7% (1)
- C13% (2)
- D7% (1)
Explanation
The syllabus explains that supervised learning requires correctly labeled data so the algorithm can learn the relationship between input features and output labels: "In supervised learning, the algorithm creates the ML model from labeled data during the training phase. The labeled data is used to infer the relationship between the input data and output
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