ML Fundamentals
Meta-Learning
Teaching an AI how to learn faster, so it can pick up new tasks with minimal examples or training.
Definition
Machine learning techniques that improve a model's ability to learn new tasks quickly by leveraging experience from previous tasks. Often called "learning to learn."
Why it matters
Enables AI systems to adapt to new domains rapidly without starting from scratch every time.
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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