What are the disadvantages of using Keras?

The question is about Keras

Answer:

One of the main disadvantages of using Keras is its limited flexibility when compared to lower-level frameworks like TensorFlow or PyTorch. Complex custom architectures can be challenging to implement in Keras. Additionally, while it simplifies model development, its high-level abstraction can sometimes obscure the finer details of the underlying processes, which may be a drawback for advanced users seeking precise control. Keras also relies heavily on its TensorFlow backend, limiting its standalone capabilities.

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