Artificial Neural Networks (ANNs) are computational models inspired by biological neural networks in the human brain used in tasks like image recognition, natural language processing, and autonomous systems. They consist of neurons, layers, weights, biases, activation functions, and iteration. ANNs work through forward propagation, loss calculation, backpropagation, and iteration. Types of ANN include forward neural networks (FNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), radial basis function networks (RBFNs), generative adversarial networks (GANs), and transformer networks. Applications of ANNs include image and video processing, natural language processing, healthcare, finance, autonomous systems, gaming, and recommendation systems.
As AI technology advances, ANNs will play a significant role in shaping intelligent systems. For more information, visit the Learn CPlusPlus.
