A Unified Theory of Neural Network Learning

af Priya Desai

A unified theory of neural network learning is a comprehensive framework that can explain how all types of neural networks learn, from the simplest perceptrons to the most complex deep learning models. It would provide a unified understanding of the different learning algorithms used in neural networks, as well as the different types of data that neural networks can learn from. Such a theory would have a number of benefits. First, it would help us to design better neural networks. By understandi... (Læs mere)