Keras Overview
Keras is a powerful deep learning API designed with developers in mind, prioritizing human readability and efficiency over machine complexity. It focuses on speeding up debugging, enhancing code elegance and conciseness, and ensuring easy maintainability and deployability for your AI projects. With Keras, you write less code, make it more readable, and accelerate your development cycles. It embraces a versatile multi-backend approach, giving you the freedom to seamlessly build and deploy models across JAX, TensorFlow, and PyTorch ecosystems. Keras is a trusted tool, powering everything from cutting-edge research at CERN and NASA to self-driving vehicles at Waymo.
Keras Key Features
- Human-Centric Design: Keras is crafted to maximize developer productivity, emphasizing fast debugging, elegant and concise code, and straightforward maintenance and deployment.
- Multi-Framework Versatility: Enjoy the flexibility to work across JAX, TensorFlow, and PyTorch, allowing you to build models that adapt effortlessly and leverage the unique strengths of each framework.
- KerasHub Model Library: Access a rich collection of Keras 3 implementations for popular model architectures like GEMMA, LLAMA, Stable Diffusion, and Mistral, complete with pretrained checkpoints for both training and inference.
- Comprehensive Developer Resources: Utilize detailed guides to master model building with the functional API, efficiently train and evaluate models using built-in methods, and customize layers through subclassing.
- Extensive Code Examples: Dive into practical examples covering diverse applications, including computer vision (image classification, object detection), natural language processing (text classification, machine translation), and generative deep learning (diffusion models, GANs).
- Industry and Research Trust: Rely on a framework trusted by top scientific organizations like CERN and NASA, as well as innovators like Waymo, for robust research and critical production applications.