
The Math Behind Supervised Learning: Making AI Less Mysterious
Last Updated on February 26, 2025 by Editorial Team
Author(s): Aleti Adarsh
Originally published on Towards AI.
Ever Wondered How AI ‘Learns’? Let’s Break It Down!
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Have you ever looked at AI models and thought, “How the heck does this thing actually learn?” You’re not alone. Supervised learning, a cornerstone of machine learning, often seems like magic — like feeding a computer some data and watching it miraculously predict things. But beneath the surface, it’s all math — yes, the stuff many of us feared in school!
If the mere mention of linear algebra and probability makes you want to run for the hills, stick around. I promise I’ll make it painless (and maybe even fun!). Think of this as a friendly chat where we untangle the numbers that power AI — because if you understand the math, you unlock the real secrets of machine learning.
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Before we dive into the numbers, let’s set the stage. Supervised learning is like training a pet — you reward it when it gets something right and correct it when it messes up.
Imagine teaching a toddler to recognize apples and oranges. You show them a picture of an apple and say, “This is an apple.” Then you show an orange and say, “This… Read the full blog for free on Medium.
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Published via Towards AI