A neural network implementation can be a nice addition to a Python programmer's skill set. If you're new to Python, examining a neural network implementation is a great way to learn the language.

Italian researchers recently developed the first functioning quantum neural network by running a special algorithm on an actual quantum computer. The team, lead by Francesco Tacchino of the ...

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder ...

Quantum resources for artificial intelligence Memristors are thought to be valuable in neural networks, which typically require large amounts of training data to operate effectively. An architecture ...

For example, when using the quantum processor to reconstruct lightning data, they found it did a better job at lower altitudes but was generally comparable to the classical neural network.

Combining quantum computing with neural networks could produce AI that can make very complex decisions quickly.

Neural network trained to solve quantum mechanical problems Trained on quantum mechanics, the network handles multi-body wavefunctions.

James McCaffrey uses cross entropy error via Python to train a neural network model for predicting a species of iris flower.