AI-900 Question 126
Single answerA retail company wants to implement a machine learning model to predict product demand across different regions. The data science team has limited expertise in hyperparameter tuning and feature engineering. Which capability of automated machine learning (AutoML) would make it most suitable for their needs?
- A
Automated selection of the best machine learning algorithm for the dataset
- B
Ability to manually tune hyperparameters for better performance
- C
Automation of feature engineering processes such as handling missing values and encoding categorical variables
- D
Requirement for extensive coding to implement machine learning pipelines
Show answer and explanation
Correct answer: A
Explanation
AutoML is designed to simplify the machine learning process by automating tasks such as algorithm selection, hyperparameter tuning, and certain aspects of feature engineering. For a team with limited expertise, its ability to automatically identify the best algorithm and optimize it makes it a highly suitable solution. This eliminates the need for in-depth knowledge of machine learning algorithms and their configurations.
- A. Correct.
Automated selection of the best machine learning algorithm for the dataset is one of the key capabilities of AutoML, making it suitable for teams with limited expertise.
- B. Incorrect.
Manually tuning hyperparameters is not a primary focus of AutoML, as the purpose of AutoML is to automate such tasks.
- C. Incorrect.
Although AutoML can handle certain aspects of feature engineering, this alone does not define its suitability for a team with limited expertise.
- D. Incorrect.
AutoML does not require extensive coding; it is designed to simplify machine learning tasks for users with minimal coding experience.