Types Of Deep Learning
Feedforward Neural Networks (FNNs)
Simple networks where information flows one direction, used for classification and regression with fixed input and output sizes.
Convolutional Neural Networks (CNNs)
Networks designed to detect spatial hierarchies in images using convolutional layers, ideal for image recognition and computer vision tasks.
Recurrent Neural Networks (RNNs)
Networks processing sequential data by maintaining memory, excellent for language modeling, speech recognition, and time-series prediction tasks.
Generative Adversarial Network (GANs)
Models that learn data distribution to generate new samples or extract features, useful in unsupervised learning and data augmentation.