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Keras

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description Keras Overview

Keras is a high-level API that simplifies the development of neural networks. Initially designed as a wrapper for TensorFlow, it now supports multiple backends, including TensorFlow, PyTorch, and JAX. Keras's focus on user-friendliness and modularity allows developers to quickly build and experiment with complex models. It's an excellent choice for both beginners and experienced practitioners who want to accelerate their deep learning workflows without delving into the intricacies of lower-level frameworks.

help Keras FAQ

What is Keras used for?

Keras is a high-level Python API for building, training, evaluating, and saving neural networks. Its familiar workflow includes layers, models, optimizers, losses, and methods such as fit and evaluate.

Which backends does Keras 3 support?

Keras 3 supports TensorFlow, JAX, and PyTorch as primary backends. The same high-level Keras model code can therefore be used with different machine-learning ecosystems, subject to backend-specific limitations.

Is Keras the same thing as TensorFlow?

No. Keras is an API, while TensorFlow is one possible backend for executing Keras models. Keras 3 is deliberately multi-backend, so a project can use PyTorch or JAX instead of TensorFlow.

What must I install before using Keras 3?

You need Keras 3 plus at least one backend such as TensorFlow, JAX, or PyTorch. The backend is selected through Keras configuration, so installing Keras alone does not provide the numerical engine needed to train a model.

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