Attention Mechanisms in Deep Learning

Learn the fundamental concepts and mechanisms of attention in deep learning through this comprehensive lecture that explores how attention mechanisms enable models to focus on relevant parts of input data, covering the mathematical foundations, different types of attention (self-attention, cross-attention, multi-head attention), and their applications in transformer architectures and various neural network models.