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Amazon AWS-Certified-Machine-Learning-Specialty: AWS Certified Machine Learning - Specialty

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Question 1

A retail company wants to combine its customer orders with the product description data from its product catalog. The structure and format of the records in each dataset is different. A data analyst tried to use a spreadsheet to combine the datasets, but the effort resulted in duplicate records and records that were not properly combined. The company needs a solution that it can use to combine similar records from the two datasets and remove any duplicates.
Which solution will meet these requirements?

A. Use an AWS Lambda function to process the dat

B. Use two arrays to compare equal strings in the fields from the two datasets and remove any duplicates.

C. Create AWS Glue crawlers for reading and populating the AWS Glue Data Catalo

D. Call the AWS Glue SearchTables API operation to perform a fuzzy-matching search on the two datasets, and cleanse the data accordingly.

E. Create AWS Glue crawlers for reading and populating the AWS Glue Data Catalo

F. Use the FindMatches transform to cleanse the data.

G. Create an AWS Lake Formation custom transfor

H. Run a transformation for matching products from the Lake Formation console to cleanse the data automatically.

Correct Answer:D

Question 2

The chief editor for a product catalog wants the research and development team to build a machine learning system that can be used to detect whether or not individuals in a collection of images are wearing the company's retail brand. The team has a set of training data.
Which machine learning algorithm should the researchers use that BEST meets their requirements?

A. Latent Dirichlet Allocation (LDA)

B. Recurrent neural network (RNN)

C. K-means

D. Convolutional neural network (CNN)

Correct Answer:D

Question 3

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. Normalize all words by making the sentence lowercase

C. Remove stop words using an English stopword dictionary.

D. Correct the typography on "quck" to "quick."

E. One-hot encode all words in the sentence

F. Tokenize the sentence into words.

Correct Answer:BCF

Question 4

A Machine Learning Specialist is preparing data for training on Amazon SageMaker The Specialist is transformed into a numpy .array, which appears to be negatively affecting the speed of the training
What should the Specialist do to optimize the data for training on SageMaker'?

A. Use the SageMaker batch transform feature to transform the training data into a DataFrame

B. Use AWS Glue to compress the data into the Apache Parquet format

C. Transform the dataset into the Recordio protobuf format

D. Use the SageMaker hyperparameter optimization feature to automatically optimize the data

Correct Answer:C

Question 6

A Machine Learning Specialist is configuring automatic model tuning in Amazon SageMaker
When using the hyperparameter optimization feature, which of the following guidelines should be followed to improve optimization?
Choose the maximum number of hyperparameters supported by

A. Amazon SageMaker to search the largest number of combinations possible

B. Specify a very large hyperparameter range to allow Amazon SageMaker to cover every possible value.

C. Use log-scaled hyperparameters to allow the hyperparameter space to be searched as quickly as possible

D. Execute only one hyperparameter tuning job at a time and improve tuning through successive rounds of experiments