Concept graph
Glossary
Short definitions with deeper context and cross-links to sibling terms.
Deep Learning
Artificial Neural Network (ANN)
A computational model inspired by the way biological neural networks function.
Training Techniques
Backpropagation
An algorithm used for training neural networks by calculating gradients of the loss function.
Deep Learning
Batch Normalization
A technique to improve training speed and stability in deep neural networks by normalizing the inputs of each layer.
Deep Learning
convolutional-neural-network
A class of deep neural networks primarily used for image processing tasks.
Machine Learning
Deep Learning
A subfield of machine learning that uses neural networks with many layers.
Regularization
Dropout
A regularization technique used to prevent overfitting in neural networks by randomly deactivating a fraction of neurons during training.
Deep Learning
Generative Adversarial Network
A class of machine learning frameworks where two neural networks contest with each other to create new data instances.
Machine Learning
Neural Network
A computational model inspired by the way biological neural networks in the human brain work.
hybrid AI
neural-symbolic-integration
A hybrid approach that combines neural networks with symbolic reasoning.
Deep Learning
recurrent-neural-network
A class of neural networks designed for processing sequences of data.
machine-learning
sparce-activation
A technique in neural networks that activates only a small subset of neurons for each input.