Problem with using DLIB (Neural Network)
Consider a function with 200 inputs and 150 outputs, so it is a very complex function and i want to model it with Deep Neural Network which has 200 inputs and 150 outputs. My task is to train such a NN(Neural network) to model this function.
After training save the trained NN somewhere. And call the saved NN instead of that function whenever it needed.
I've already prepared the dataset and targets samples which are saved in .csv files.
Thus far i was using Python's Tensorflow lib. And it worked greatly. For some reasons i should implemented it in C++ as well. I've been looking for c++ deep learning library and found DLIB.
Unfortunately i could not find any useful or efficient tutorials for that (neither Dlib documentation).
Could you please share your experience (implementation steps or piece of codes or pseudo codes)? Any help with will greatly appreciated.
Summary: model a complex function with NN in C++.
Regards.
After training save the trained NN somewhere. And call the saved NN instead of that function whenever it needed.
I've already prepared the dataset and targets samples which are saved in .csv files.
Thus far i was using Python's Tensorflow lib. And it worked greatly. For some reasons i should implemented it in C++ as well. I've been looking for c++ deep learning library and found DLIB.
Unfortunately i could not find any useful or efficient tutorials for that (neither Dlib documentation).
Could you please share your experience (implementation steps or piece of codes or pseudo codes)? Any help with will greatly appreciated.
Summary: model a complex function with NN in C++.
Regards.
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