Keras has several advantages as a deep learning library, including:
User-friendly API: Keras provides a simple and intuitive interface that allows developers to quickly build and train deep learning models without having to write complex code.
Flexibility: Keras is a highly flexible library that can run on top of multiple backends, including TensorFlow, CNTK, and Theano. This means that developers can choose the best backend for their specific use case and easily switch between backends if needed.
Extensibility: Keras allows developers to create custom layers, loss functions, and metrics, making it easy to extend the library for specific use cases.
Pre-built models: Keras provides a wide range of pre-built models that can be easily adapted to specific use cases. This makes it easy for developers to get started with deep learning and experiment with different architectures.
Portability: Keras models can be easily saved and loaded, making it easy to deploy models in production environments or share them with other developers.
Overall, Keras provides a powerful and flexible toolset for building deep learning models, making it an ideal choice for both beginners and experienced developers alike.
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