Neural-network building blocks · MLD-0804
Neural network
A parameterized computation built from interconnected layers or units whose outputs are learned from data.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Map image pixels to category scores.
Original caveat
Biological inspiration does not imply a faithful model of the brain.
Context and aliases
Level: Foundational. Stages: Training · Inference · Theory.
Tags: DL · SLM · LLM · Vision · NLP.
Aliases: Artificial neural network · ANN.
Related concepts
Concepts linking here
Technology connections
- Burn — Rust-native deep-learning framework.
- Equinox — JAX library representing models as PyTrees.
- Flax — Neural-network library built on JAX.
- JAX — Composable automatic differentiation, vectorization and compilation for numerical Python.
- Keras — High-level model-building API supporting multiple numerical backends.
- MLX — Array and ML framework optimized for Apple silicon.
- PyTorch — Tensor computation, automatic differentiation and neural-network framework.
- TensorFlow — Tensor and neural-network framework with deployment tooling.
- tinygrad — Compact tensor and automatic-differentiation framework.
Original references
- Deep Learning: online textbook ↗ · Consulted
- PyTorch neural-network layers ↗ · Reference link
- PyTorch documentation ↗ · Reference link
- Original reference URL ↗