The key characteristics of deep learning are:
- Multiple layers: Deep learning models consist of multiple layers, each of which is composed of a set of artificial neurons or nodes.
- Non-linear transformations: Each layer applies a non-linear transformation to the input data, allowing the model to learn complex relationships between features.
- Hierarchical representations: Deep learning models learn to represent data at multiple levels of abstraction, from low-level features to high-level concepts.
- Large amounts of data: Deep learning models require large amounts of data to learn and improve their performance.