HOT AMAZON MLS-C01 VERIFIED ANSWERS & TRUSTABLE EXAM-KILLER - LEADER IN CERTIFICATION EXAM MATERIALS

Hot Amazon MLS-C01 Verified Answers & Trustable Exam-Killer - Leader in Certification Exam Materials

Hot Amazon MLS-C01 Verified Answers & Trustable Exam-Killer - Leader in Certification Exam Materials

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The AWS Certified Machine Learning - Specialty exam requires a deep understanding of the AWS platform, including its services, features, and functionality. MLS-C01 Exam covers a wide range of topics, including data preparation, feature engineering, model selection and evaluation, deployment, and monitoring. It also covers various machine learning techniques, such as supervised learning, unsupervised learning, and reinforcement learning.

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Amazon AWS Certified Machine Learning - Specialty Sample Questions (Q87-Q92):

NEW QUESTION # 87
A Machine Learning Specialist at a company sensitive to security is preparing a dataset for model training.
The dataset is stored in Amazon S3 and contains Personally Identifiable Information (Pll). The dataset:
* Must be accessible from a VPC only.
* Must not traverse the public internet.
How can these requirements be satisfied?

  • A. Create a VPC endpoint and use Network Access Control Lists (NACLs) to allow traffic between only the given VPC endpoint and an Amazon EC2 instance.
  • B. Create a VPC endpoint and apply a bucket access policy that allows access from the given VPC endpoint and an Amazon EC2 instance.
  • C. Create a VPC endpoint and use security groups to restrict access to the given VPC endpoint and an Amazon EC2 instance.
  • D. Create a VPC endpoint and apply a bucket access policy that restricts access to the given VPC endpoint and the VPC.

Answer: B


NEW QUESTION # 88
A machine learning specialist stores IoT soil sensor data in Amazon DynamoDB table and stores weather event data as JSON files in Amazon S3. The dataset in DynamoDB is 10 GB in size and the dataset in Amazon S3 is 5 GB in size. The specialist wants to train a model on this data to help predict soil moisture levels as a function of weather events using Amazon SageMaker.
Which solution will accomplish the necessary transformation to train the Amazon SageMaker model with the LEAST amount of administrative overhead?

  • A. Crawl the data using AWS Glue crawlers. Write an AWS Glue ETL job that merges the two tables and writes the output to an Amazon Redshift cluster.
  • B. Launch an Amazon EMR cluster. Create an Apache Hive external table for the DynamoDB table and S3 data. Join the Hive tables and write the results out to Amazon S3.
  • C. Enable Amazon DynamoDB Streams on the sensor table. Write an AWS Lambda function that consumes the stream and appends the results to the existing weather files in Amazon S3.
  • D. Crawl the data using AWS Glue crawlers. Write an AWS Glue ETL job that merges the two tables and writes the output in CSV format to Amazon S3.

Answer: C


NEW QUESTION # 89
A data engineer at a bank is evaluating a new tabular dataset that includes customer dat a. The data engineer will use the customer data to create a new model to predict customer behavior. After creating a correlation matrix for the variables, the data engineer notices that many of the 100 features are highly correlated with each other.
Which steps should the data engineer take to address this issue? (Choose two.)

  • A. Apply one-hot encoding category-based variables.
  • B. Remove a portion of highly correlated features from the dataset.
  • C. Apply principal component analysis (PCA).
  • D. Apply min-max feature scaling to the dataset.
  • E. Use a linear-based algorithm to train the model.

Answer: C,D

Explanation:
Reference:
https://scikit-learn.org/stable/auto_examples/preprocessing/plot_all_scaling.html


NEW QUESTION # 90
A monitoring service generates 1 TB of scale metrics record data every minute. A Research team performs queries on this data using Amazon Athena. The queries run slowly due to the large volume of data, and the team requires better performance.
How should the records be stored in Amazon S3 to improve query performance?

  • A. Parquet files
  • B. CSV files
  • C. RecordIO
  • D. Compressed JSON

Answer: A


NEW QUESTION # 91
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. Clustering
  • C. Classification
  • D. Reinforcement learning

Answer: C

Explanation:
The goal of classification is to determine to which class or category a data point (customer in our case) belongs to. For classification problems, data scientists would use historical data with predefined target variables AKA labels (churner/non-churner) ?answers that need to be predicted ?to train an algorithm.
With classification, businesses can answer the following questions:
Will this customer churn or not?
Will a customer renew their subscription?
Will a user downgrade a pricing plan?
Are there any signs of unusual customer behavior?
https://www.kdnuggets.com/2019/05/churn-prediction-machine-learning.html


NEW QUESTION # 92
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