Exam DP-100 topic 3 question 186 discussion

Actual exam question from Microsoft's DP-100

Question #: 186
Topic #: 3

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You manage an Azure Machine Learning workspace.

You plan to train a natural language processing (NLP) model that will assign labels for designated tokens in unstructured text.

You need to configure the NLP task by using automated machine learning.

Which configuration values should you use? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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by jefimija at Oct. 23, 2024, 1:23 p.m.

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Secure_Defense

2 months, 2 weeks ago

Answers are correct: - Named Entity Recognition (NER) "There are multiple possible tags for tokens in sequences. The task is to predict the tags for all the tokens for each sequence. For example, extracting domain-specific entities from unstructured text, such as contracts or financial documents." Ref: https://learn.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-nlp-models?view=azureml-api-2&tabs=python#select-your-nlp-task - CoNLL "Unlike multi-class or multi-label, which takes .csv format datasets, named entity recognition requires CoNLL format. The file must contain exactly two columns and in each row, the token and the label is separated by a single space." Ref: https://learn.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-nlp-models?view=azureml-api-2&tabs=python#named-entity-recognition-ner

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Fefnut

5 months ago

- Multi-label text classification because " model that will assign labels for designated tokens in unstructured text" implying there can be multiple labels for tokens. - CSV because it's the format for NLP multi-label task. https://learn.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-nlp-models?view=azureml-api-2&tabs=python

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