•1 min read•from Machine Learning
Bayesian Opt. GPs vs Linear models and Neural Networks for parameter optimizations [R]
Hi,
Relatively new to deep learning. I wanted some opinions on which of these approaches might be best for time series data and spectral analysis. I currently use a GP and it works pretty well, but I’m wondering what the computational tradeoffs and so forth might be. Any ideas?
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