Keras is a deep learning api designed for human beings, not machines. Keras focuses on debugging speed, code elegance & conciseness, maintainability, and deployability. Read our keras developer guides.
Are you looking for tutorials showing keras in action across a wide range of use cases? See the keras code examples: Keras 3 is a full rewrite of keras that enables you to run your keras workflows on top of either jax, tensorflow, pytorch, or openvino (for inference-only), and that unlocks brand new large-scale.
They're one of the best ways to become a keras expert. Keras follows the principle of progressive disclosure of complexity: Preprocessing utilities backend utilities scikit-learn api wrappers keras configuration utilities keras 3 api documentation models api layers api callbacks api ops api optimizers metrics losses data.
They should demonstrate modern keras best practices. Jul 10, 2023introduction keras 3 is a deep learning framework works with tensorflow, jax, and pytorch interchangeably. This notebook will walk you through key keras 3 workflows.
Keras applications are deep learning models that are made available alongside pre-trained weights. The library provides keras 3 implementations of popular model architectures, paired with a collection of pretrained checkpoints available on kaggle models. Models can be used for both training and.
