ML Fundamentals
Clustering
Automatically grouping similar data points together without being told the categories, the AI discovers the structure.
Definition
An unsupervised learning technique that partitions data into groups (clusters) where items within a group are more similar to each other than to items in other groups. Includes K-means, DBSCAN, and hierarchical methods.
Why it matters
Powers customer segmentation, anomaly detection, and pattern discovery when you don't know what groups exist in your data.
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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