Keras
Keras is an open-source deep learning framework designed for humans, supporting TensorFlow, JAX and PyTorch backends with a consistent, modular API and rich pretrained models. It serves everyone from beginners to advanced developers building and deploying models.
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Suitable for developers and researchers who want a clean API to build, train and deploy deep learning models fast; not suitable for users who want a no-code, purely graphical tool.
Verified facts
What is Keras
Keras is an open-source deep learning framework designed for humans, supporting TensorFlow, JAX and PyTorch backends with a consistent, modular API and rich pretrained models. It serves everyone from beginners to advanced developers building and deploying models.
Key features of Keras
- Developers prototyping neural networks quickly with the Sequential or Functional API
- Researchers reusing the same model code across TensorFlow, JAX and PyTorch backends
- Engineers applying transfer learning with pretrained models to image recognition tasks
- Teams saving trained models and deploying them for production inference
Good for
- Cross-framework compatibility across TensorFlow, JAX and PyTorch backends
- Simple, consistent, modular API with low learning cost and composable components
- Open source and free, with thorough documentation and many pretrained models
Watch out
- Requires Python programming ability and basic deep learning concepts
- High-level abstraction limits low-level customization compared with raw backends
- Extreme performance tuning still requires diving into backend-native capabilities
How to use Keras
- Install Keras with pip and choose a backend framework
- Define the model with the Sequential or Functional API
- Compile the model with an optimizer, loss function and metrics
- Prepare and preprocess data, then train with the fit method
- Evaluate, predict with new data, and save the model for later use
Who Keras is for
Difficulty: Intermediate
- Developers prototyping neural networks quickly with the Sequential or Functional API
- Researchers reusing the same model code across TensorFlow, JAX and PyTorch backends
- Engineers applying transfer learning with pretrained models to image recognition tasks
- Teams saving trained models and deploying them for production inference
FAQ
Is Keras free?
Yes. Keras is an open-source deep learning framework, completely free to use, with its code hosted in the keras-team repository on GitHub.
Which backends does Keras support?
Keras supports TensorFlow, JAX and PyTorch, and developers can switch between these frameworks seamlessly while keeping the same model code.
Which modeling API should beginners start with?
Keras offers the Sequential API and the Functional API. Beginners should start with Sequential to build simple linear stacks of layers, then move to Functional for multi-input, multi-output or residual architectures.
Sources and verification
Sources: keras.io (opens in a new tab)
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