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: over 150 well-explained notebooks …

They're one of the best ways to become a Keras expert. Most of our guides are written as Jupyter notebooks and can be run in one click in Google Colab, a hosted notebook environment that …

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 …

They should be shorter than 300 lines of code (comments may be as long as you want). They should demonstrate modern Keras best practices. They should be substantially different in …

Structured data preprocessing utilities Tensor utilities Python & NumPy utilities Scikit-Learn API wrappers Keras configuration utilities Keras 3 API documentation Models API Layers API …

Keras follows the principle of progressive disclosure of complexity: it makes it easy to get started, yet it makes it possible to handle arbitrarily advanced use cases, only requiring incremental …

Keras Applications are deep learning models that are made available alongside pre-trained weights. These models can be used for prediction, feature extraction, and fine-tuning.

Jul 10, 2023 · Introduction Keras 3 is a deep learning framework works with TensorFlow, JAX, and PyTorch interchangeably. This notebook will walk you through key Keras 3 workflows.

outputs: The output (s) of the model: a tensor that originated from keras.Input objects or a combination of such tensors in a dict, list or tuple. See Functional API example below.