Would you suggest to me a new way of modeling heterogeneous data with deep learning?
See here:
https://team.inria.fr/parietal/research/statistical-and-machine-learning-methods-for-large-scale-data/learning-from-heterogeneous-data/
Article TensorFlow: Large-Scale Machine Learning on Heterogeneous Di...
https://www.aaai.org/ocs/index.php/AAAI/AAAI16/paper/viewPDFInterstitial/12036/11603
http://193.6.4.39/~czap/letoltes/IS14/IS2014/PDF/AUTHOR/IS141025.PDF
http://repository.ittelkom-pwt.ac.id/1059/1/DeepMob%20Learning%20Deep%20Knowledge%20of%20Human%20Emergency%20Behavior%20and%20Mobility%20from%20Big%20and%20Heterogeneous%20Data.pdf
https://ieeexplore.ieee.org/abstract/document/6993854/
Raw Data is need to be noramized and resized (you may use PCA for data pre-processing) according to the model, before processing via prediction models.
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