AI-900: Clustering Applications in Machine Learning

Learn how to identify scenarios that can be resolved by applying clustering modules/algorithms in machine learning. This is a sample question for the AI-900 certification exam.

Question

Which of the following scenarios can be resolved by applying clustering modules/algorithms?

Select all that apply.

A. A bike rental company that wants to predict the number of customers for the next day so that it will assure the necessary staff and cycles.
B. A radio company that wants to apply tags (like rock, pop, R&B etc) to songs or artists.
C. A social media company that wants to group similar users based on their posts.

Answer

B. A radio company that wants to apply tags (like rock, pop, R&B etc) to songs or artists.
C. A social media company that wants to group similar users based on their posts.

Explanation

Clustering models have the purpose of separating similar data points into intuitive groups.

The correct answer is B and C. Clustering is a type of unsupervised machine learning that groups data points based on their similarity. Clustering can be used to discover patterns, categories, or segments in the data without having any prior labels or classifications.

Some examples of clustering applications are:

• B. A radio company that wants to apply tags (like rock, pop, R&B etc) to songs or artists. Clustering can help the radio company to automatically assign genres or labels to songs or artists based on their audio features, such as tempo, pitch, rhythm, etc. This can help the radio company to create playlists, recommendations, or personalized stations for their listeners.
• C. A social media company that wants to group similar users based on their posts. Clustering can help the social media company to identify communities or segments of users who share similar interests, opinions, or preferences based on their posts, comments, likes, etc. This can help the social media company to target ads, offer promotions, or enhance user experience.

A scenario that cannot be resolved by applying clustering is:

• A. A bike rental company that wants to predict the number of customers for the next day so that it will assure the necessary staff and cycles. This is a regression problem, not a clustering problem. Regression is a type of supervised machine learning that predicts a continuous numerical value based on the input features. The bike rental company needs to use historical data of customer demand and other factors, such as weather, season, holidays, etc., to train a regression model that can forecast the number of customers for the next day.

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