The Golden Goose Deep Learning AI Neural Network
Is a proprietary engine developed by our team to be able to trade in and out of different types of investments with continual microtransactions based on patterns it can identify from deep learning. Our developers and analysts work together to teach the “Brain” by entering the proper data points needed to make the right decisions. Once the “Brain” is taught all the data points needed to start trading it will continue to learn on its own, with the data continually being fed in by the team.
Difference Between AI and Neural Network
AI refers to any machine that can mimic human cognitive skills. Neural networks, on the other hand, refer to a network of artificial neurons or nodes vaguely inspired by the biological neural networks that constitute the human brain.
A neural network is a method within artificial intelligence that teaches computers to process data in a way that is inspired by the human brain. It is a type of machine learning process, called deep learning, that uses interconnected nodes or neurons in a layered structure that resembles the human brain. Artificial neural networks (ANNs) gather their knowledge by detecting the patterns and relationships in data and learn (or are trained) through experience, not from programming.
What is the difference between deep learning and neural networks?
Deep learning systems can have several layers, whereas neural networks normally have only a few. Deep learning algorithms are now more powerful and capable of learning more complicated patterns in data. Deep learning techniques also demand more data and processing capacity to train than neural networks.