Visual AWS-Certified-Machine-Learning-Specialty Cert Test, AWS-Certified-Machine-Learning-Specialty Exam Fees

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To become an AWS Certified Machine Learning - Specialty, you need to have a deep understanding of machine learning concepts, algorithms, and tools. You should also have practical experience in building and deploying machine learning models using AWS services such as Amazon SageMaker, AWS Lambda, Amazon Redshift, and Amazon Athena. AWS-Certified-Machine-Learning-Specialty Exam covers various topics such as data preparation, feature engineering, model training and deployment, optimization and tuning, and security and compliance. It consists of multiple-choice and multiple-response questions, and you have 170 minutes to complete it. Passing the exam requires a score of at least 750 out of 1000. By earning the AWS Certified Machine Learning - Specialty certification, you demonstrate your ability to design and deliver cutting-edge machine learning solutions on the AWS platform, which can open up new career opportunities and increase your earning potential.

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ThreeFormats of ActualCollection Amazon AWS-Certified-Machine-Learning-Specialty Practice Test Questions

These Amazon AWS-Certified-Machine-Learning-Specialty exam practice questions will greatly help you to prepare well for the final AWS-Certified-Machine-Learning-Specialty certification exam. Amazon AWS-Certified-Machine-Learning-Specialty exam preparation and boost your confidence to pass the AWS-Certified-Machine-Learning-Specialty Exam. All Amazon AWS-Certified-Machine-Learning-Specialty exam practice test questions contain the real and updated Amazon AWS-Certified-Machine-Learning-Specialty exam practice test questions.

Amazon MLS-C01 certification exam is designed to test the knowledge and skills of candidates who are interested in becoming an AWS Certified Machine Learning Specialist. AWS-Certified-Machine-Learning-Specialty Exam is intended to validate the candidate's ability to design, implement, deploy, and maintain machine learning solutions for a variety of business use cases. AWS-Certified-Machine-Learning-Specialty exam is suitable for individuals who have a deep understanding of machine learning algorithms, statistical modeling, data analysis, and data preprocessing techniques.

Amazon MLS-C01 (AWS Certified Machine Learning - Specialty) Certification Exam is a highly sought-after certification in the field of Machine Learning. It is designed for individuals who have a strong understanding of machine learning concepts and techniques and are interested in showcasing their expertise in this domain. AWS Certified Machine Learning - Specialty certification is specifically designed for professionals who are interested in building, deploying, and maintaining machine learning solutions on Amazon Web Services (AWS) platform.

Amazon AWS Certified Machine Learning - Specialty Sample Questions (Q71-Q76):

NEW QUESTION # 71
A Mobile Network Operator is building an analytics platform to analyze and optimize a company's operations using Amazon Athena and Amazon S3.
The source systems send data in .CSV format in real time. The Data Engineering team wants to transform the data to the Apache Parquet format before storing it on Amazon S3.
Which solution takes the LEAST effort to implement?

A. Ingest .CSV data using Apache Kafka Streams on Amazon EC2 instances and use Kafka Connect S3 to serialize data as Parquet
B. Ingest .CSV data from Amazon Kinesis Data Streams and use Amazon Kinesis Data Firehose to convert data into Parquet.
C. Ingest .CSV data from Amazon Kinesis Data Streams and use Amazon Glue to convert data into Parquet.
D. Ingest .CSV data using Apache Spark Structured Streaming in an Amazon EMR cluster and use Apache Spark to convert data into Parquet.

Answer: C

Explanation:
1. Use Glue Crawler to build scheme from the structured csv file.
2. Configure and run a job to transform the data from CSV to Parquet.
https://aws.amazon.com/blogs/big-data/build-a-data-lake-foundation-with-aws-glue-and-amazon- s3/

NEW QUESTION # 72
A Mobile Network Operator is building an analytics platform to analyze and optimize a company's operations using Amazon Athena and Amazon S3 The source systems send data in CSV format in real lime The Data Engineering team wants to transform the data to the Apache Parquet format before storing it on Amazon S3 Which solution takes the LEAST effort to implement?

A. Ingest .CSV data using Apache Kafka Streams on Amazon EC2 instances and use Kafka Connect S3 to serialize data as Parquet
B. Ingest .CSV data from Amazon Kinesis Data Streams and use Amazon Kinesis Data Firehose to convert data into Parquet.
C. Ingest .CSV data from Amazon Kinesis Data Streams and use Amazon Glue to convert data into Parquet.
D. Ingest .CSV data using Apache Spark Structured Streaming in an Amazon EMR cluster and use Apache Spark to convert data into Parquet.

Answer: B

Explanation:
Explanation
Amazon Kinesis Data Streams is a service that can capture, store, and process streaming data in real time.
Amazon Kinesis Data Firehose is a service that can deliver streaming data to various destinations, such as Amazon S3, Amazon Redshift, or Amazon Elasticsearch Service. Amazon Kinesis Data Firehose can also transform the data before delivering it, such as converting the data format, compressing the data, or encrypting the data. One of the supported data formats that Amazon Kinesis Data Firehose can convert to is Apache Parquet, which is a columnar storage format that can improve the performance and cost-efficiency of analytics queries. By using Amazon Kinesis Data Streams and Amazon Kinesis Data Firehose, the Mobile Network Operator can ingest the .CSV data from the source systems and use Amazon Kinesis Data Firehose to convert the data into Parquet before storing it on Amazon S3. This solution takes the least effort to implement, as it does not require any additional resources, such as Amazon EC2 instances, Amazon EMR clusters, or Amazon Glue jobs. The solution can also leverage the built-in features of Amazon Kinesis Data Firehose, such as data buffering, batching, retry, and error handling.
References:
Amazon Kinesis Data Streams - Amazon Web Services
Amazon Kinesis Data Firehose - Amazon Web Services
Data Transformation - Amazon Kinesis Data Firehose
Apache Parquet - Amazon Athena

NEW QUESTION # 73
An insurance company is developing a new device for vehicles that uses a camera to observe drivers' behavior and alert them when they appear distracted. The company created approximately 10,000 training images in a controlled environment that a Machine Learning Specialist will use to train and evaluate machine learning models.
During the model evaluation, the Specialist notices that the training error rate diminishes faster as the number of epochs increases and the model is not accurately inferring on the unseen test images.
Which of the following should be used to resolve this issue? (Choose two.)

A. Make the neural network architecture complex.
B. Add L2 regularization to the model.
C. Add vanishing gradient to the model.
D. Use gradient checking in the model.
E. Perform data augmentation on the training data.

Answer: B,E

Explanation:
The model must have been overfitted. Regularization helps to solve the overfitting problem in machine learning (as well as data augmentation).

NEW QUESTION # 74
A manufacturing company stores production volume data in a PostgreSQL database.
The company needs an end-to-end solution that will give business analysts the ability to prepare data for processing and to predict future production volume based the previous year's production volume. The solution must not require the company to have coding knowledge.
Which solution will meet these requirements with the LEAST effort?

A. Use AWS Glue DataBrew to read the data that is in the PostgreSQL database and to perform the data preparation. Use Amazon SageMaker Studio for the prediction modeling.
B. Use AWS Database Migration Service (AWS DMS) to transfer the data from the PostgreSQL database to an Amazon S3 bucket. Create an Amazon EMR cluster to read the S3 bucket and perform the data preparation. Use Amazon SageMaker Studio for the prediction modeling.
C. Use AWS Database Migration Service (AWS DMS) to transfer the data from the PostgreSQL database to an Amazon S3 bucket. Use AWS Glue to read the data in the S3 bucket and to perform the data preparation. Use Amazon SageMaker Canvas for the prediction modeling.
D. Use AWS Glue DataBrew to read the data that is in the PostgreSQL database and to perform the data preparation. Use Amazon SageMaker Canvas for the prediction modeling.

Answer: D

Explanation:
AWS Glue DataBrew provides a no-code data preparation interface that enables business analysts to clean and transform data from various sources, including PostgreSQL databases, without needing programming skills. Amazon SageMaker Canvas offers a no-code interface for machine learning model training and predictions, allowing users to predict future production volume without coding expertise.
This solution meets the requirements efficiently by providing end-to-end data preparation and prediction modeling without requiring coding.

NEW QUESTION # 75
A large mobile network operating company is building a machine learning model to predict customers who are likely to unsubscribe from the service. The company plans to offer an incentive for these customers as the cost of churn is far greater than the cost of the incentive.
The model produces the following confusion matrix after evaluating on a test dataset of 100 customers:
Based on the model evaluation results, why is this a viable model for production?

A. The model is 86% accurate and the cost incurred by the company as a result of false positives is less than the false negatives.
B. The precision of the model is 86%, which is greater than the accuracy of the model.
C. The model is 86% accurate and the cost incurred by the company as a result of false negatives is less than the false positives.
D. The precision of the model is 86%, which is less than the accuracy of the model.

Answer: C

NEW QUESTION # 76
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Visual AWS-Certified-Machine-Learning-Specialty Cert Test, AWS-Certified-Machine-Learning-Specialty Exam Fees

ThreeFormats of ActualCollection Amazon AWS-Certified-Machine-Learning-Specialty Practice Test Questions

Amazon AWS Certified Machine Learning - Specialty Sample Questions (Q71-Q76):

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