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Machine learning: When to use each method and technique


You’re probably hearing more and more about machine learning, a subset of artificial intelligence. But what exactly can you do with machine learning?

The technology encompasses a number of methods and techniques, and each has a set of potential use cases. Enterprises would do well to examine them before plunging ahead with plans to invest in machine learning tools and infrastructure.

Machine learning methods

Supervised learning

Supervised learning is ideal if you know what you want a machine to learn. You can expose it to an enormous set of training data, examine the output, and tweak parameters until you get the results you expect. Later, you can see what the machine has learned by having it predict the results for a set of validation data it hasn’t seen before.



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