Supervised Learning is a way of teaching computers to do certain tasks.
Imagine you’re trying to learn how to identify different kinds of fruits. You have a helpful teacher who shows you a fruit, tells you what it is – say, “This is an apple” – and explains how to recognize it. Your teacher does this with many different kinds of fruits, and over time, you learn to identify them on your own. That’s a bit like supervised learning.
In supervised learning, we have a computer program, called a model, that we want to teach to do something, like recognize images of fruits. We show the model many different images of fruits, and for each image, we also provide the correct answer, or label (like “apple”, “banana”, or “cherry”). The model learns from these examples.
The “supervision” comes from us knowing the correct answer (the label) for each example we show the model. The model’s job is to learn from these examples so that in the future, when it sees a new fruit image it hasn’t seen before, it can correctly identify the fruit.
Supervised learning is used in many areas of artificial intelligence, including image recognition, speech recognition, and natural language processing.
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