Neural Networks vs. Deep Learning
eWeek, Thursday, August 24,2023
Neural networks and deep learning are closely related artificial intelligence technologies. While they are often used in tandem, there are key differences between them:
Neural networks are a subset of machine learning, which is a technique used to help computers learn using training that is modeled on results gleaned from large data sets. As such, neural networks are an attempt mimic human thinking, specifically how biological neurons are thought to signal to one another. The Google search engine, with its many interrelated nodes, is a good best example of a neural network. It is probably the largest in existence as it has the task of providing the instant and accurate results that users demand.
Deep learning could be defined as a form of machine learning that is firmly based on AI neural networks. In some ways, deep learning can be viewed as advanced neural networks as it takes the basic capabilities of neural networks to a whole new level.