what will be the future of Machine Learning as a Service?

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Machine learning (ML) is the study of computer algorithms that automatically improve through experience. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model based on sample data called "training data" to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or impossible to develop traditional algorithms to perform the required tasks.

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Machine learning is closely related to computer statistics, which focuses on making predictions using computers. The study of mathematical optimization provides methods, theory and areas of application in the field of machine learning. Data mining is a related research area that focuses on exploratory data analysis through unsupervised learning. When applied to business problems, machine learning is also known as predictive analytics.

In machine learning, computers discover how to perform tasks without being specifically programmed to do so. Computers learn from the data provided in order to carry out certain tasks. For simple tasks assigned to computers, algorithms can be programmed to tell the machine how to perform all of the steps necessary to solve the problem at hand. No learning is required from the computer. For more advanced tasks, it can be difficult for a human to manually create the necessary algorithms. In practice, helping the machine develop its own algorithm can be more effective than having human programmers specify each step required.

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The machine learning discipline uses different approaches to teach computers to perform tasks for which a fully satisfactory algorithm is not available. In cases where there are a large number of potential answers, one approach is to mark some of the correct answers as valid. This can then be used as training data for the computer to improve the algorithms used to determine the correct answers. For example, to train a system for the task of digital character recognition, the MNIST data set of handwritten digits was often used.

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