MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Unsupervised machine learning can identify previously unknown patterns in data. It can be easier, faster and less costly to use than supervised learning as unsupervised learning does not require the manual work associated with labeling data that supervised learning requires.

Detailed explanation-2: -The short answer to this question is: yes! Unlabeled data can be successfully used in ML even though its scope of use is relatively smaller, and commonly requires further annotation of the data or part of the elements to have labels. Still, unlabeled data is an effective and useful tool for developing your AI.

Detailed explanation-3: -What is unsupervised learning? Unsupervised learning, also known as unsupervised machine learning, uses machine learning algorithms to analyze and cluster unlabeled datasets. These algorithms discover hidden patterns or data groupings without the need for human intervention.

Detailed explanation-4: -Advantages of unsupervised machine learning include: Requires less manual data preparation (i.e., no hand labeling) than supervised machine learning. Capable of finding previously unknown patterns in data, which is impossible with supervised machine learning models.

Detailed explanation-5: -Supervised machine learning is generally used to classify data or make predictions, whereas unsupervised learning is generally used to understand relationships within datasets. Supervised machine learning is much more resource-intensive because of the need for labelled data.