NLP - Sequence Models for NLPWhich of the following best describes the gating mechanism in a GRU?AIt uses reset and update gates to manage memory contentBIt uses max pooling to select important featuresCIt applies dropout to prevent overfittingDIt uses attention weights to focus on wordsCheck Answer
Step-by-Step SolutionSolution:Step 1: Recall GRU internal structureGRU has two gates: reset gate and update gate to control memory.Step 2: Differentiate from other mechanismsMax pooling and attention are different techniques; dropout is regularization.Final Answer:It uses reset and update gates to manage memory content -> Option AQuick Check:GRU gates = reset + update [OK]Quick Trick: GRU gates are reset and update, not pooling or attention [OK]Common Mistakes:MISTAKESMixing GRU gates with attention mechanismsConfusing dropout with gatingThinking max pooling is part of GRU
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