Learn what machine learning is, how it works, and what are some of its applications in the real world. Find out the difference between machine learning and other types of artificial intelligence.
Table of Contents
Question
What is machine learning?
A. Artificial intelligence technology that can produce various types of content
B. Programs or systems that learn from data instead of being explicitly programmed
C. Algorithms used to describe and create new data
D. Large, general-purpose language models
Answer
B. Programs or systems that learn from data instead of being explicitly programmed
Explanation
Machine learning is a branch of artificial intelligence that uses algorithms trained on data sets to create self-learning models that are capable of predicting outcomes and classifying information without human intervention. Machine learning is used today for a wide range of commercial purposes, such as suggesting products to consumers based on their past purchases, predicting stock market fluctuations, and translating text from one language to another.
The other options are not accurate definitions of machine learning, as they are either too narrow or too broad:
- Artificial intelligence technology that can produce various types of content. This option is too broad, as it encompasses other types of artificial intelligence technology that are not machine learning, such as expert systems, natural language processing, or computer vision.
- Algorithms used to describe and create new data. This option is too narrow, as it only covers one aspect of machine learning, which is generative modeling. Machine learning also includes other types of tasks, such as classification, regression, clustering, or reinforcement learning.
- Large, general-purpose language models. This option is also too narrow, as it only refers to a specific type of machine learning model that is used for natural language processing. Machine learning models can also be used for other domains, such as image processing, speech recognition, or recommendation systems.
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