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Analysis of Sequence Model Outputs for Different Tasks
Consider two different applications for a sequence model. Task A is to autocomplete a user's sentence by predicting the most likely next word. Task B is to classify an entire email as either 'spam' or 'not spam'. Compare and contrast the expected structure of the final output from the sequence model for Task A versus Task B. Explain the reasoning behind these structural differences based on the goal of each task.
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Ch.1 Pre-training - Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
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Analysis of Sequence Model Outputs for Different Tasks
A data scientist is working with a sequence model,
g(·; θ), for two different projects. In Project A, the goal is to predict the most likely next word in a user's search query. In Project B, the goal is to classify an entire product review as either 'positive' or 'negative'. How would the nature of the model's direct output,o, most likely differ between these two projects?A data scientist is developing two different systems. Match each system's primary task with the most likely structure of its underlying model's direct output.