<ul><li>An attention mechanism is a computational process that helps models prioritize the most important parts of the input data when making predictions.</li><li>Attention mechanisms address challenges faced by traditional models like RNNs by enabling models to attend to relevant parts of the input.</li><li>The attention mechanism has three key components: score calculation, normalization, and weighted sum.</li><li>Attention mechanisms are widely used in various fields including natural language processing, computer vision, speech recognition, and healthcare.</li></ul>

Day 58: Attention Mechanisms — Foundation of Transformer Models

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