Deep learning algorithms can be segregated into four different branches based on their area of research and application:
General deep learning algorithms: Densely-connected layers or fully-connected networks
Sequence models: Recurrent Neural Networks (RNN), Long Short Term Memory (LSTM) Networks, Gated Recurrent Units, etc
Spatial data models: Convolutional Neural Networks (CNN), Generative Adversarial Networks (GAN)
Other algorithms: Unsupervised Learning, Reinforcement Learning (RL), Sparse Encoding, etc
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