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NEW QUESTION 38
An agency collects census information within a country to determine healthcare and social program needs by province and city. The census form collects responses for approximately 500 questions from each citizen Which combination of algorithms would provide the appropriate insights? (Select TWO )

• A. The principal component analysis (PCA) algorithm
• B. The factorization machines (FM) algorithm
• C. The k-means algorithm g The Random Cut Forest (RCF) algorithm
• D. The Latent Dirichlet Allocation (LDA) algorithm

Answer: A

NEW QUESTION 39
A term frequency-inverse document frequency (tf-idf) matrix using both unigrams and bigrams is built from a text corpus consisting of the following two sentences:
1. Please call the number below.
2. Please do not call us.
What are the dimensions of the tf-idf matrix?

• A. (2, 8)
• B. (2, 16)
• C. (8, 10)
• D. (2, 10)

Answer: B

Explanation:
There are 2 sentences, 8 unique unigrams, and 8 unique bigrams, so the result would be (2,16).
The phrases are "Please call the number below" and "Please do not call us." Each word individually (unigram) is "Please," "call," "the," "number," "below," "do," "not," and "us." The unique bigrams are "Please call," "call the," "the number," "number below," "Please do," "do not," "not call," and "call us."

NEW QUESTION 40
A Machine Learning Specialist is working with a large company to leverage machine learning within its products. The company wants to group its customers into categories based on which customers will and will not churn within the next 6 months. The company has labeled the data available to the Specialist.
Which machine learning model type should the Specialist use to accomplish this task?

• A. Linear regression
• B. Reinforcement learning
• C. Classification
• D. Clustering

Answer: A

NEW QUESTION 41
A Machine Learning Specialist is creating a new natural language processing application that processes a dataset comprised of 1 million sentences The aim is to then run Word2Vec to generate embeddings of the sentences and enable different types of predictions - Here is an example from the dataset
"The quck BROWN FOX jumps over the lazy dog "
Which of the following are the operations the Specialist needs to perform to correctly sanitize and prepare the data in a repeatable manner? (Select THREE)

• A. Perform part-of-speech tagging and keep the action verb and the nouns only
• B. Tokenize the sentence into words.
• C. Normalize all words by making the sentence lowercase
• D. Correct the typography on "quck" to "quick."
• E. One-hot encode all words in the sentence
• F. Remove stop words using an English stopword dictionary.

Answer: A,D,E

NEW QUESTION 42
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?

• A. Amazon SageMaker BlazingText cbow mode
• B. Amazon Comprehend syntax analysis and entity detection
• C. Scikit-leam term frequency-inverse document frequency (TF-IDF) vectorizer
• D. Natural Language Toolkit (NLTK) stemming and stop word removal

Answer: C

Explanation:
https://monkeylearn.com/sentiment-analysis/

NEW QUESTION 43
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