MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values.

Detailed explanation-2: -Traditional data science methods can handle the first process layer: converting raw data into information. Machine learning can now help extract knowledge from information. Machine learning algorithms find context in information by recognizing patterns, grouping, or classifying information.

Detailed explanation-3: -Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing.

Detailed explanation-4: -What is true about Machine Learning? The main focus of ML is to allow computer systems to learn from experience without being explicitly programmed or human intervention. ML is a type of artificial intelligence that extracts patterns out of raw data by using an algorithm or method.