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Achieving the AWS Certified Machine Learning – Specialty certification can open up a range of job opportunities in the field of machine learning, including roles such as Machine Learning Engineer, Data Scientist, and AI Developer. It also provides a solid foundation for pursuing advanced certifications in the field of machine learning on AWS.

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Amazon AWS Certified Machine Learning - Specialty Sample Questions (Q40-Q45):

NEW QUESTION # 40
A Data Scientist is training a multilayer perception (MLP) on a dataset with multiple classes. The target class of interest is unique compared to the other classes within the dataset, but it does not achieve and acceptable recall metric. The Data Scientist has already tried varying the number and size of the MLP's hidden layers, which has not significantly improved the results. A solution to improve recall must be implemented as quickly as possible.
Which techniques should be used to meet these requirements?

A. Add class weights to the MLP's loss function and then retrainB. Gather more data using Amazon Mechanical Turk and then retrainC. Train an XGBoost model instead of an MLPD. Train an anomaly detection model instead of an MLP

Answer: C

NEW QUESTION # 41
A financial services company is building a robust serverless data lake on Amazon S3. The data lake should be flexible and meet the following requirements:
* Support querying old and new data on Amazon S3 through Amazon Athena and Amazon Redshift Spectrum.
* Support event-driven ETL pipelines
* Provide a quick and easy way to understand metadata
Which approach meets these requirements?

A. Use an AWS Glue crawler to crawl S3 data, an AWS Lambda function to trigger an AWS Batch job, and an external Apache Hive metastore to search and discover metadata.B. Use an AWS Glue crawler to crawl S3 data, an AWS Lambda function to trigger an AWS Glue ETL job, and an AWS Glue Data catalog to search and discover metadata.C. Use an AWS Glue crawler to crawl S3 data, an Amazon CloudWatch alarm to trigger an AWS Glue ETL job, and an external Apache Hive metastore to search and discover metadata.D. Use an AWS Glue crawler to crawl S3 data, an Amazon CloudWatch alarm to trigger an AWS Batch job, and an AWS Glue Data Catalog to search and discover metadata.

Answer: B

NEW QUESTION # 42
A Machine Learning Specialist must build out a process to query a dataset on Amazon S3 using Amazon Athena The dataset contains more than 800.000 records stored as plaintext CSV files Each record contains 200 columns and is approximately 1 5 MB in size Most queries will span 5 to 10 columns only How should the Machine Learning Specialist transform the dataset to minimize query runtime?

A. Convert the records to JSON formatB. Convert the records to XML formatC. Convert the records to GZIP CSV formatD. Convert the records to Apache Parquet format

Answer: D

Explanation:
Using compressions will reduce the amount of data scanned by Amazon Athena, and also reduce your S3 bucket storage. It's a Win-Win for your AWS bill. Supported formats: GZIP, LZO, SNAPPY (Parquet) and ZLIB.

NEW QUESTION # 43
During mini-batch training of a neural network for a classification problem, a Data Scientist notices that training accuracy oscillates What is the MOST likely cause of this issue?

A. The learning rate is very highB. Dataset shuffling is disabledC. The class distribution in the dataset is imbalancedD. The batch size is too big

Answer: A

NEW QUESTION # 44
An interactive online dictionary wants to add a widget that displays words used in similar contexts. A Machine Learning Specialist is asked to provide word features for the downstream nearest neighbor model powering the widget.
What should the Specialist do to meet these requirements?

A. Download word embedding's pre-trained on a large corpus.B. Create word embedding factors that store edit distance with every other word.C. Produce a set of synonyms for every word using Amazon Mechanical Turk.D. Create one-hot word encoding vectors.

Answer: A

NEW QUESTION # 45
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