Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
- Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
- The process of learning begins with observations or data, such as examples, direct experience, or instruction,
- in order to look for patterns in data and make better decisions in the future based on the examples that we provide.
- The primary aim is to allow the computers learn automatically without human intervention or assistance and adjust actions accordingly.
- But, using the classic algorithms of machine learning, text is considered as a sequence of keywords; instead, an approach based on semantic analysis mimics the human ability to understand the meaning of a text.
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Machine learning (ML) is the study of computer algorithms that improve automatically through experience.
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It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so.
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Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or infeasible to develop conventional algorithms to perform the needed tasks.
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Machine learning is closely related to computational statistics, which focuses on making predictions using computers.
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The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning.
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Data mining is a related field of study, focusing on exploratory data analysis through unsupervised learning.
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In its application across business problems, machine learning is also referred to as predictive analytics.
