Training Neural Networks Theory of Practical Issues

Through the work conducted concerning the implementation of neural networks, some theoretical issues emerged. This work arises from the need to explore these issues, covering the main topics grounding the learning process and data processing. A review is provided on adequate methods of data normalization, synaptic weights normalization and initialization, window width estimation, activation functions selection, saturation and overfitting prevention and calibration of other parameters.