Editing Deep Learning (section)

== Types of Deep Learning Architectures ==

=== Convolutional Neural Networks (CNNs) ===
Used primarily for image recognition and classification. They extract spatial hierarchies of features using convolutional layers.

* Example: Face detection, medical imaging

=== Recurrent Neural Networks (RNNs) ===
Designed for sequence data like time series or language. They maintain internal memory to model temporal behavior.

* Example: Language translation, speech recognition

=== Long Short-Term Memory (LSTM) ===
A special kind of RNN capable of learning long-term dependencies.

=== Generative Adversarial Networks (GANs) ===
Consist of two networks (generator and discriminator) competing to create realistic synthetic data.

* Example: AI-generated art, deepfakes

=== Transformers ===
Used heavily in [[Natural Language Processing]], transformers replace recurrence with self-attention mechanisms.

* Example: GPT, BERT