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Machine learning works like this: features are like baskets of things we give to the machine to help it learn. These components, known as features, help the computer understand what it's looking at or what needs to do next. When designing features for machine learning, we can choose things like eye color or nose shape so the computer can recognize faces more accurately. In certain cases, we may need to alter existing features or create new ones using math or special techniques which enhance understanding of existing ones - this helps the machine process information faster and more accurately. | Machine learning works like this: features are like baskets of things we give to the machine to help it learn. These components, known as features, help the computer understand what it's looking at or what needs to do next. When designing features for machine learning, we can choose things like eye color or nose shape so the computer can recognize faces more accurately. In certain cases, we may need to alter existing features or create new ones using math or special techniques which enhance understanding of existing ones - this helps the machine process information faster and more accurately. | ||
[[Category:Terms]] [[Category:Machine learning terms]] | [[Category:Terms]] [[Category:Machine learning terms]] [[Category:not updated]] | ||