Neural Networks are a type of artificial intelligence that uses interconnected layers of nodes to process data and make predictions. They are inspired by the structure and function of the human brain.
Neural networks are a type of artificial intelligence (AI) that is modeled after the human brain. They are composed of interconnected nodes, or neurons, that are designed to process information in a similar way to the neurons in the human brain. Neural networks are used to solve complex problems that are too difficult for traditional computing methods.
Neural networks are composed of layers of interconnected nodes, or neurons. Each neuron is connected to other neurons in the network, and the connections between neurons are weighted. The weights determine how much influence each neuron has on the output of the network. The neurons are organized into layers, and each layer is responsible for a different task. The input layer receives data from the outside world, the hidden layers process the data, and the output layer produces the desired result.
Neural networks are trained using a process called backpropagation. This process involves adjusting the weights of the connections between neurons in order to minimize the error between the desired output and the actual output of the network. This process is repeated until the network is able to accurately predict the desired output.
Neural networks are used in a variety of applications, including image recognition, natural language processing, and robotics. They are also used in medical diagnosis, financial forecasting, and autonomous vehicles. Neural networks are becoming increasingly popular due to their ability to solve complex problems that are too difficult for traditional computing methods.