Hyper-parameters optimization using Bayesian optimization for LSTM regression program specifically for No. of network layers, No. of hidden units, and learning rate.

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Dear Experts,
I need to perform Hyperparameters optimization using Bayesian optimization for my deep learning LSTM regression program. On Matlab, a solved example is only given for deep learning CNN classification program in which section depth, momentum etc are optimized. I have read all answers on MATLAB Answers for my LSTM program but no any clear guideline. I need to optimize No. of network layers, No. of hidden units, and learning rate. Please help me for this. Thank You
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