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AI-900: Clustering in Machine Learning: Supervised or Unsupervised?

Learn the difference between supervised and unsupervised machine learning, and why clustering is an example of unsupervised machine learning. Prepare for the AI-900 certification exam with this informative guide.

Question

Clustering is an example of supervised machine learning, in which you train a model to separate items into clusters based purely on their characteristics or features. True or False?

A. True
B. False

Answer

B. False

Explanation

Clustering is an example of unsupervised machine learning, in which you train a model to separate items into clusters based purely on their characteristics or features.

The correct answer is B. False. Clustering is an example of unsupervised machine learning, in which you train a model to separate items into clusters based purely on their characteristics or features.

Supervised machine learning is a type of machine learning that involves training a model with labeled data, which means the data has a known outcome or target variable. For example, you can train a model to classify images of animals by providing labeled images of cats, dogs, and other animals. The model learns from the labels and can then predict the label for a new image.

Unsupervised machine learning is a type of machine learning that involves training a model with unlabeled data, which means the data does not have a known outcome or target variable. For example, you can train a model to cluster customers based on their purchase history, without knowing in advance how many clusters there are or what they represent. The model learns from the data and can then assign a cluster label to each customer.

Clustering is a common technique in unsupervised machine learning that groups items based on their similarity or distance in a feature space. For example, you can cluster customers based on their age, income, and spending habits. The model does not know the meaning or purpose of the clusters, but it can identify patterns and trends in the data.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump

Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook

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