artificial neural networks
Machine learning architecture
Artificial neural networks are computing systems loosely modeled on biological brains, using layers of interconnected nodes that process information and adjust their connections through training.
They power most modern machine learning—image recognition, language translation, recommendation algorithms.
The architecture allows systems to learn patterns from data rather than following explicit programming: The neural network learned to identify cats after processing millions of images.
- deep learningLayered neural network methods
- layersStacked levels or coatings
- backpropagationReverse gradient computation method
- weightsHeavy objects for lifting
- trainingDeveloping abilities through practice
training data · perceptron · nodes · activation · synapses · machine learning · convolutional · recurrent · hidden layers · vanishing gradient · learning rate · feedforward · forward pass · bias · epoch · overfitting · pattern recognition · image recognition
artificial neural networkshuman brain
Neural organ enabling cognition
cerebral cortex · wetware · neurons · nervous systems · gray matter
artificial neural networksexpert systems
AI using encoded rules
artificial neural networkslinear regression
Statistical straight-line fitting method
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