MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -One practical example of supervised learning problems is predicting house prices. How is this achieved? First, we need data about the houses: square footage, number of rooms, features, whether a house has a garden or not, and so on. We then need to know the prices of these houses, i.e. the corresponding labels.

Detailed explanation-2: -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.

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: -Supervised learning is a subset of artificial intelligence and machine learning. It is also known as Supervised machine learning. And is defined by its ability to train algorithms to categorize data and predict outcomes accurately. Moreover, it teaches computer systems to find hidden insights using the available data.