Machine Learning
Machine learning is a way of building software where the algorithm tunes its own internal numbers from examples, instead of a programmer writing every rule. You supply data and correct answers; the finished product is a model that predicts on inputs it has never seen.
No jargon, no math
In plain words, what is it?
Classic software: a human writes the rules, data goes in, answers come out. Machine learning flips the arrows. You give the computer examples, inputs with the right answers attached, and an algorithm adjusts millions of internal numbers to shrink the error, pass after pass. What falls out is a model. Show it a new invoice and it predicts the category; show it a new sensor trace and it predicts the fault. It works because real data repeats patterns. The boundary: the model learns your data, gaps and biases included. Outside the territory your examples cover, its confidence is decoration.
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Examples in. You collect pairs: inputs plus the correct answers (labels).
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Training. The algorithm adjusts internal numbers to shrink the error, pass after pass.
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Validation. Held-back data tests the model; bad results send you back for more data.
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Model out. The finished file does one job: input in, prediction out.
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Prediction. New data flows through; the model answers in milliseconds.
Terms that live nearby.
Algorithm
An algorithm is a finite, unambiguous sequence of steps that solves a class of problems: a recipe that takes an input, applies rules, and always produces an output. Every piece of software, AI included, is algorithms all the way down.
ReadTraining
Training is the process that turns an untrained model into a working AI: you feed it thousands or millions of examples, compare its guesses with the correct answers, and nudge its internal settings until the guesses get good.
ReadDataset
A dataset is the organised collection of examples an AI learns from or is judged on: thousands or millions of rows of text, images or sensor readings, cleaned, labelled and split into training, validation and test parts.
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