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Название: Machine Learning Mathematics: Explore Deep Learning Using Data Science. How to Create Artificial Intelligence Using Statistics, Algorithms, Analysis, and Data Mining Concepts (2022 Beginners Guide)
Автор: Jackson Smart
Издательство: Amazon.com Services LLC
Год: 2021
Страниц: 167
Язык: английский
Формат: pdf, azw3, epub
Размер: 10.2 MB
The concept of Artificial Intelligence technology is based on the idea that computers can be programmed to have human-like intelligence. It can mimic human reasoning and learning abilities, adapting to new inputs and completing tasks without human intervention. The Artificial Intelligence principle includes Machine Learning. Machine Learning Technology (ML) is an Artificial Intelligence philosophy that focuses on computers' designed ability to learn directly and self-train, discover information patterns to improve the underlying algorithm, and make autonomous decisions without human intervention. During his tenure at IBM, Arthur Samuel, a pioneering gaming and artificial intelligence professor, coined the term "machine learning" in 1959. According to Machine Learning theory, modern computers can be trained using specific training data sets that can be easily customized to achieve desired functionality. Machine Learning is guided by a pattern-recognition method in which prior interactions and outcomes are recorded and reviewed in a way that correlates to its current position. Due to the iterative nature of machine learning, computers must be able to adapt to new data without the assistance of a human because they are required to process infinite volumes of data. Statistics, which focuses on making predictions using modern computer tools and technologies, is inextricably linked to machine learning. The study of "mathematical optimization" adds methodologies, theories, and application areas to the field of Machine Learning.
Автор: Jackson Smart
Издательство: Amazon.com Services LLC
Год: 2021
Страниц: 167
Язык: английский
Формат: pdf, azw3, epub
Размер: 10.2 MB
The concept of Artificial Intelligence technology is based on the idea that computers can be programmed to have human-like intelligence. It can mimic human reasoning and learning abilities, adapting to new inputs and completing tasks without human intervention. The Artificial Intelligence principle includes Machine Learning. Machine Learning Technology (ML) is an Artificial Intelligence philosophy that focuses on computers' designed ability to learn directly and self-train, discover information patterns to improve the underlying algorithm, and make autonomous decisions without human intervention. During his tenure at IBM, Arthur Samuel, a pioneering gaming and artificial intelligence professor, coined the term "machine learning" in 1959. According to Machine Learning theory, modern computers can be trained using specific training data sets that can be easily customized to achieve desired functionality. Machine Learning is guided by a pattern-recognition method in which prior interactions and outcomes are recorded and reviewed in a way that correlates to its current position. Due to the iterative nature of machine learning, computers must be able to adapt to new data without the assistance of a human because they are required to process infinite volumes of data. Statistics, which focuses on making predictions using modern computer tools and technologies, is inextricably linked to machine learning. The study of "mathematical optimization" adds methodologies, theories, and application areas to the field of Machine Learning.