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Machine learning is based on algorithms that can learn from data without rules-based programming. One reason it’s become so valuable is that companies are dealing with vast and rapidly growing volumes of data. Some estimates suggest that the amount of data globally doubles every two years.
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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.
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Supervised, unsupervised and reinforcement Machine Learning basically are a description of ways in which you can let machines or algorithms loose on a data set. The machines would also be expected to learn something useful out of the process. Supervised, unsupervised and reinforcement learning lead the way into the future of machines that is expected to be bright, and will over time assist humans
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Machine learning is based on algorithms that can learn from data without rules-based programming. One reason it’s become so valuable is that companies are dealing with vast and rapidly growing volumes of data. Some estimates suggest that the amount of data globally doubles every two years.
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