Keras
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Introduction
Keras is a deep learning API designed for human beings, not machines, focusing on debugging speed, code elegance, and maintainability.
Listed on
July 22, 2026
What is Keras?
Keras is a high-level deep learning API that runs on top of JAX, TensorFlow, and PyTorch. It is designed to be user-friendly, allowing developers to build, train, and deploy neural networks with minimal code. Keras emphasizes code elegance, conciseness, and maintainability, making it a popular choice for both research and production.
How to use Keras?
- To get started with Keras, install it via pip: `pip install --upgrade keras`. You also need to install a backend framework (JAX, TensorFlow, or PyTorch). Configure your backend by setting the `KERAS_BACKEND` environment variable or editing `~/.keras/keras.json`. Then, you can build models using the Sequential API, Functional API, or by subclassing layers. Train and evaluate models using built-in methods like `model.fit()` and `model.evaluate()`. For advanced use cases, explore developer guides and code examples on the Keras website.
Core features of Keras
- Multi-backend support: JAX, TensorFlow, and PyTorch
- High-level API for building neural networks
- Built-in training and evaluation methods
- Support for custom layers and models via subclassing
- Extensive documentation and code examples
- Integration with KerasHub for pretrained models
- Tools for hyperparameter tuning (KerasTuner) and model deployment
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