Topic 1 Question 64
A Data Scientist is working on an application that performs sentiment analysis. The validation accuracy is poor, and the Data Scientist thinks that the cause may be a rich vocabulary and a low average frequency of words in the dataset. Which tool should be used to improve the validation accuracy?
Amazon Comprehend syntax analysis and entity detection
Amazon SageMaker BlazingText cbow mode
Natural Language Toolkit (NLTK) stemming and stop word removal
Scikit-leam term frequency-inverse document frequency (TF-IDF) vectorizer
解説
Reference: https://monkeylearn.com/sentiment-analysis/
ユーザの投票
コメント(17)
D is correct. Amazon Comprehend syntax analysis =/= Amazon Comprehend sentiment analysis. You need to read choices very carefully.
👍 32tap1232021/09/23AWS COMPREHEND IS A NATURAL LANGUAGE PROCESSING (NLP) SERVICE THAT USES MACHINE LEARNING TO DISCOVER INSIGHTS FROM TEXT. AMAZON COMPREHEND PROVIDES KEYPHRASE EXTRACTION, SENTIMENT ANALYSIS, ENTITY RECOGNITION, TOPIC MODELING, AND LANGUAGE DETECTION APIS SO YOU CAN EASILY INTEGRATE NATURAL LANGUAGE PROCESSING INTO YOUR APPLICATIONS.
HTTPS://AWS.AMAZON.COM/COMPREHEND/FEATURES/?NC1=H_LS
JUST THROUGH AMAZON COMPREHEND IS MUCH EASY THAN OTHER THE MUCH MORE CONVENIENT ANSWER IS A.
👍 22DonaldCMLIN2021/09/21Its B!! Blazing text has out-of-vocabulary (OOV) feature which can embed the non vocabulary words. https://docs.aws.amazon.com/sagemaker/latest/dg/blazingtext.html
👍 9srinu30542021/10/29
シャッフルモード