Keras is a high-level deep learning API used to design, build, and train neural networks for tasks such as computer vision, natural language processing, and time series forecasting. It provides a framework for defining model architectures and optimizing weights through a structured interface.
The project is defined by a backend-agnostic design that allows the same model code to run across different compute engines. This multi-backend execution enables users to swap underlying engines to optimize for specific hardware or performance requirements.
The system supports distributed model training to scale workloads from local machines to clusters of accelerators. It includes capabilities for managing deep learning data pipelines with diverse dataset formats and provides a pluggable architecture for integrating custom layers, models, and metrics.
