Machine Learning (영어버전)

소개

"Machine Learning (영어버전)"에 대한 내용입니다.

목차

1. Introduction
2. How Machines can learn
3. Neural Networks
4. Convolutional Neural Networks

본문내용

Machine learning is a method of data analysis that automates analytical model building. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make predictions with minimal human intervention.

Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or impractical for humans to write explicit rules. Other examples include stock trading, drug discovery and manufacturing, and fraud detection.

Machine learning is also a research field in computer science, dealing with the question of how to create computers that learn. It has been described as "the scientific study of the algorithms that make it possible for computers to improve automatically through experience."

The term "machine learning" was coined in 1959 by Arthur Samuel, an American IBMer and pioneer in the field of computer gaming and artificial intelligence. Samuel defined it as a "field of study that gives computers the ability to learn without being explicitly programmed."

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