ML Fundamentals
Deep Learning
AI powered by neural networks with many layers, capable of learning incredibly complex patterns from massive amounts of data.
Definition
A subset of machine learning that uses neural networks with multiple layers (hence "deep") to automatically learn hierarchical representations from data. Powers modern AI breakthroughs in vision, language, and speech.
Why it matters
The engine behind virtually every major AI breakthrough since 2012, from AlexNet to GPT-4.
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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