ML Fundamentals
Classification
Teaching an AI to sort things into categories, like "spam" or "not spam," "high-risk deal" or "likely to close."
Definition
A supervised learning task where the model predicts which category or class an input belongs to. Binary classification (two classes) and multi-class classification (many classes) are common variants.
Why it matters
One of the most widely deployed ML tasks, powers spam filters, medical diagnosis, deal scoring, and fraud detection.
Related terms in ML Fundamentals
Activation Functions
The "switch" inside a neural network that decides whether a neuron should fire, allowing the AI to learn complex non-linear patterns.
Active Learning
A technique where the AI asks humans to label only the most confusing examples, saving time and money on data labeling.
Anomaly Detection
Finding the "weird" stuff in a dataset, like a credit card charge in a foreign country or a broken machine part.
Artificial General Intelligence (AGI)
A hypothetical "super-AI" that can learn and do any intellectual task a human can do, not just one specific thing.
From vocabulary to outcomes
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