Artificial Neural Network 1.8

✴In information technology, a neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain. Neural networks -- also called artificial neural networks -- are a variety of deep learning technologies.☆

►Artificial neural networks are forecasting methods that are based on simple mathematical models of the brain. They allow complex nonlinear relationships between the response variable and its predictors.☆

►Artificial neural networks (ANNs) are statistical models directly inspired by, and partially modeled on biological neural networks. They are capable of modeling and processing nonlinear relationships between inputs and outputs in parallel.☆

►Neural Network Architecture. Humans and other animals process information with neural networks. These are formed from trillions of neurons (nerve cells) exchanging brief electrical pulses called action potentials. ... This neural network is formed in three layers, called the input layer, hidden layer, and output layer.☆

❰ A deep neural network (DNN) is an ANN with multiple hidden layers between the input and output layers. Similar to shallow ANNs, DNNs can model complex non-linear relationships. ❱

【Topics Covered in this App are Listed Below】

⇢ Basic Concepts
⇢ Building Blocks
⇢ Learning and Adaptation
⇢ Supervised Learning
⇢ Unsupervised Learning
⇢ Learning Vector Quantization
⇢ Adaptive Resonance Theory
⇢ Kohonen Self-Organizing Feature Maps
⇢ Associate Memory Network
⇢ Artificial Neural Network - Hopfield Networks
⇢ Boltzmann Machine
⇢ Brain-State-in-a-Box Network
⇢ Optimization Using Hopfield Network
⇢ Other Optimization Techniques
⇢ Artificial Neural Network - Genetic Algorithm
⇢ Applications of Neural Networks