Showing posts from July, 2017

Deep learning functions

Hi there,

the second part of the project is finishing. This period was quite interesting because I had to dive into the theory behind Neural Networks  In particular [1], [2], [3] and [4] were very useful and I will sum up some concepts here below. On the other hand, coding became more challenging and the focus was on the python layer and in particular the way to structure the class in order to make everything scalable and generalizable. Summarizing the situation, in the first period I implemented all the Octave classes for the user interface. Those are Matlab compatible and they call some Python function in a seamless way. On the Python side, the TensorFlow API is used to build the graph of the Neural Network and perform training, evaluation and prediction.

I implemented the three core functions: trainNetwork, SeriesNetwork and trainingOptions. To do this, I used a Python class in which I initialize an object with the graph of the network and I store this object as attribute of SeriesNe…