Machine Learning

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Machine learning is a field that focuses on developing algorithms and techniques to enable computers to automatically learn and improve from data without being explicitly programmed.

What is the purpose of machine learning?

"Machine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive."

How are problems solved in machine learning?

"the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms."

What recent advancement has had a positive impact on machine learning?

"Recently, generative artificial neural networks have been able to surpass results of many previous approaches."

In what areas have machine learning approaches been applied?

"Machine-learning approaches have been applied to large language models, computer vision, speech recognition, email filtering, agriculture and medicine."

Why is machine learning used in these areas?

"where it is too costly to develop algorithms to perform the needed tasks."

What provides the mathematical foundations of machine learning?

"The mathematical foundations of ML are provided by mathematical optimization (mathematical programming) methods."

How is data mining related to machine learning?

"Data mining is a related (parallel) field of study, focusing on exploratory data analysis through unsupervised learning."

In what business context is machine learning known as predictive analytics?

"ML is known in its application across business problems under the name predictive analytics."

Is all machine learning statistically based?

"Although not all machine learning is statistically based, computational statistics is an important source of the field's methods."

What field focuses on developing algorithms through human programming?

"the problems are solved by helping machines 'discover' their 'own' algorithms without needing to be explicitly told what to do by any human-developed algorithms."

What are some specific applications of machine learning?

"Machine-learning approaches have been applied to large language models, computer vision, speech recognition, email filtering, agriculture and medicine."

How does machine learning compare to human algorithm development in terms of cost?

"development of algorithms by human programmers would be cost-prohibitive"

What has recent research shown regarding the effectiveness of machine learning algorithms?

"generative artificial neural networks have been able to surpass results of many previous approaches."

Which other field of study is closely related to machine learning?

"Data mining is a related (parallel) field of study, focusing on exploratory data analysis through unsupervised learning."

Where has machine learning been successfully applied in the medical field?

"Machine-learning approaches have been applied to...medicine."

What are the benefits of using machine learning algorithms?

"helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms."

How is machine learning different from data mining?

"the problems are solved by helping machines 'discover' their 'own' algorithms, without needing to be explicitly told what to do by any human-developed algorithms."

What provides the theoretical basis for machine learning?

"The mathematical foundations of ML are provided by mathematical optimization (mathematical programming) methods."

Is machine learning limited to specific industries or sectors?

"where it is too costly to develop algorithms to perform the needed tasks."

What other field of study shares methods with machine learning?

"Although not all machine learning is statistically based, computational statistics is an important source of the field's methods."