By far the three most popular neural networks are:
Convolutional Neural Networks (CNNs): CNNs are among the most popular neural networks for computer vision tasks such as image recognition, object classification and object detection. They are used in applications such as self-driving cars, security systems, and medical image processing.
Recurrent Neural Networks (RNNs): RNNs are used to analyze sequences of data, such as speech and language. They can model dependencies between sequential data elements and are used for tasks such as machine translation, text generation, and speech recognition.
Generative Adversarial Networks (GANs): GANs are used to create new data by simulating existing data. They consist of two neural networks: generative and discriminative. The generative neural network creates fake data, and the discriminative neural network tries to distinguish fake data from real data. GANs are used in applications such as photo, video and music generation.