AUC
Deep Learning
Neural network components that allow models to focus on relevant parts of input data
Detailed Explanation
Attention mechanisms are neural network components that enable models to dynamically focus on the most relevant parts of input data when generating outputs. By assigning different weights to different input elements, attention helps models capture long-range dependencies and improve accuracy in tasks like translation, image recognition, and natural language processing, making them more efficient in understanding complex patterns.
Use Cases
- •Enhance language translation accuracy by enabling models to focus on relevant words, capturing context and long-range dependencies effectively.
Related Terms
Other terms in the Deep Learning category