Deep Learning hidden layers
by Pedro Perdomo 20 years ago, we implemented a virtual sensor using neural networks with no more than a couple of hidden layers. When I trained my first two-layer neural network to predict the content of methane in the bottom of a deethanizer column, I realized that more than one layer did not improve my virtual sensor results. Why no limit today in the internal or hidden layers? Why deep learning? First, computing power has been increasing, so training neural networks with many layers is now feasible. Second, why so many layers if not a big amount of data available . And third, if you just add layers, you will run into some issues, the neural networks will take a long time to train, some of the layers will become all zero and worst, no better results. Researchers have developed “tricks” and techniques to get deep neural networks to work. Neural networks with many hidden layers have enabled dramatic improvements in hard p...