As an expert in Python programming and Keras Deep Learning framework, I understand the intricacies involved in model loading, especially when your model uses a custom loss function. This article guides you on how to overcome these challenges and successfully load your Keras model with custom loss function.
Keras, a high-level neural networks API, is user-friendly and modular, capable of running on top of either TensorFlow or Theano. It’s known for its simplicity and ease of use. However, despite its simplicity, understanding certain tasks like loading a model with custom loss function can be quite difficult.