ML Fundamentals
Unsupervised Learning
Training an AI on unlabeled data to find hidden patterns and groupings, no right answers provided, just data.
Definition
A machine learning paradigm where the model learns patterns from unlabeled data without explicit target variables. Includes clustering, dimensionality reduction, and anomaly detection.
Why it matters
Essential when labeled data is unavailable, powers customer segmentation, anomaly detection, and data exploration.
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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