A branch of AI where systems learn patterns from data instead of following explicitly programmed rules.
A branch of AI where systems learn patterns from data instead of following explicitly programmed rules. Feed it enough examples and it figures out the patterns itself. Includes supervised learning (labeled data), unsupervised learning (finding structure), and reinforcement learning (learning from rewards).
A subset of machine learning that uses neural networks with many layers (hence 'deep') to learn complex patterns from large amounts of data.
The most common machine learning approach: training a model on labeled data where each example comes with the correct answer.
A computing system loosely inspired by biological brains, consisting of interconnected nodes (neurons) organized in layers.
A mathematical function applied to a neuron's output that introduces non-linearity into the network.
An optimization algorithm that combines the best parts of two other methods — AdaGrad and RMSProp.
Artificial General Intelligence.
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