Keras

Keras is a deep learning API designed for human beings, not machines. It focuses on debugging speed, code elegance and conciseness, maintainability, and deployability. With its multi-backend approach, Keras gives you the freedom to work with JAX, TensorFlow, and PyTorch, allowing models to move seamlessly across these frameworks and leverage the strengths of each ecosystem.

Key Features

• Multi-backend support: Build and train models on JAX, TensorFlow, or PyTorch with the same codebase.
• KerasHub: Provides Keras 3 implementations of popular model architectures (e.g., Gemma, Llama, Stable Diffusion, Mistral) paired with pretrained checkpoints available on Kaggle Models.
• Developer-friendly API: Emphasizes smaller, more readable, and easier-to-iterate codebases.

Who It's For

Keras is trusted for research and production by organizations such as CERN, NASA, NIH, Waymo, Google, Amazon, Spotify, Uber, and Netflix. It partners with Kaggle and HuggingFace to meet ML developers in the tools they use daily.

Use Cases

Keras is used for computer vision, natural language processing, generative deep learning, and more. The site provides extensive code examples and developer guides covering the functional API, training and evaluation with built-in methods, and making new layers and models via subclassing.

Key Benefits

• Multi-backend support (JAX, TensorFlow, PyTorch)
• Focus on debugging speed and code elegance
• Used by major research and production organizations
• Includes KerasHub for pretrained model architectures