MLS-C01模擬解説集、MLS-C01テスト内容

ちなみに、GoShiken MLS-C01の一部をクラウドストレージからダウンロードできます：https://drive.google.com/open?id=13SDzLXUhwdqfuN4gJYeRl1qViV6gtHWW

現在多くの会社では、特別なGAQM、EMC、ISC認証などを持っているなら、高い給料が得られています。我々の提供するMLS-C01問題集はあなたに試験に順調に合格することができます。試験に参加する前に、我々の模擬問題集MLS-C01資料が必要です。この問題集を選択したら、あなたは100％試験に合格することができます。

Amazon MLS -C01（AWS認定機械学習 - 専門）試験は、Amazon Web Services（AWS）プラットフォームでの機械学習に関連する知識とスキルについて個人をテストする認定試験です。この試験は、機械学習の分野で認定された専門家になり、AWSの機械学習ソリューションの設計、実装、展開、および維持の専門知識を紹介したい個人向けに設計されています。

Amazon MLS-C01試験は、AWS認定機械学習スペシャリストになることに興味がある個人向けに設計されています。この認定は、さまざまなビジネスアプリケーション向けに機械学習（ML）ソリューションを設計、実装、展開、および維持する候補者の能力を検証します。この試験では、データの準備、機能エンジニアリング、モデルの選択と評価、展開戦略など、幅広いトピックをカバーしています。

AWS Certified Machine Learning - Specialty試験は、データの準備、特徴量エンジニアリング、モデルの選択と評価、機械学習アルゴリズム、AWS上での機械学習ソリューションの展開と実装など、さまざまなトピックについての候補者の知識をテストします。この試験では、Amazon SageMaker、Amazon Comprehend、Amazon RekognitionなどのAWS機械学習サービスに関連するトピックもカバーされます。

MLS-C01模擬解説集

MLS-C01テスト内容、MLS-C01基礎訓練

話と行動の距離はどのぐらいありますか。これは人の心によることです。意志が強い人にとって、行動は目と鼻の先にあるのです。あなたはきっとこのような人でしょう。AmazonのMLS-C01認定試験に申し込んだ以上、試験に合格しなければならないです。これもあなたの意志が強いことを表示する方法です。GoShikenが提供したトレーニング資料はインターネットで最高のものです。AmazonのMLS-C01認定試験に合格したいのなら、GoShikenのAmazonのMLS-C01試験トレーニング資料を利用してください。

Amazon AWS Certified Machine Learning - Specialty 認定 MLS-C01 試験問題 (Q26-Q31):

質問 # 26
A Machine Learning Specialist is applying a linear least squares regression model to a dataset with 1 000 records and 50 features Prior to training, the ML Specialist notices that two features are perfectly linearly dependent Why could this be an issue for the linear least squares regression model?

A. It could introduce non-linear dependencies within the data which could invalidate the linear assumptions of the model
B. It could cause the backpropagation algorithm to fail during training
C. It could modify the loss function during optimization causing it to fail during training
D. It could create a singular matrix during optimization which fails to define a unique solution

正解：D

解説：
Linear least squares regression is a method of fitting a linear model to a set of data by minimizing the sum of squared errors between the observed and predicted values. The solution of the linear least squares problem can be obtained by solving the normal equations, which are given by ATAx=ATb, where A is the matrix of explanatory variables, b is the vector of response variables, and x is the vector of unknown coefficients.
However, if the matrix A has two features that are perfectly linearly dependent, then the matrix ATA will be singular, meaning that it does not have a unique inverse. This implies that the normal equations do not have a unique solution, and the linear least squares problem is ill-posed. In other words, there are infinitely many values of x that can satisfy the normal equations, and the linear model is not identifiable.
This can be an issue for the linear least squares regression model, as it can lead to instability, inconsistency, and poor generalization of the model. It can also cause numerical difficulties when trying to solve the normal equations using computational methods, such as matrix inversion or decomposition. Therefore, it is advisable to avoid or remove the linearly dependent features from the matrix A before applying the linear least squares regression model.
References:
Linear least squares (mathematics)
Linear Regression in Matrix Form
Singular Matrix Problem

質問 # 27
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. CSV files
B. RecordIO
C. Compressed JSON
D. Parquet files

正解：B

質問 # 28
A Machine Learning Specialist has completed a proof of concept for a company using a small data sample and now the Specialist is ready to implement an end-to-end solution in AWS using Amazon SageMaker The historical training data is stored in Amazon RDS Which approach should the Specialist use for training a model using that data?

A. Move the data to Amazon ElastiCache using AWS DMS and set up a connection within the notebook to pull data in for fast access.
B. Move the data to Amazon DynamoDB and set up a connection to DynamoDB within the notebook to pull data in
C. Write a direct connection to the SQL database within the notebook and pull data in
D. Push the data from Microsoft SQL Server to Amazon S3 using an AWS Data Pipeline and provide the S3 location within the notebook.

正解：D

解説：
Explanation
Pushing the data from Microsoft SQL Server to Amazon S3 using an AWS Data Pipeline and providing the S3 location within the notebook is the best approach for training a model using the data stored in Amazon RDS. This is because Amazon SageMaker can directly access data from Amazon S3 and train models on it.
AWS Data Pipeline is a service that can automate the movement and transformation of data between different AWS services. It can also use Amazon RDS as a data source and Amazon S3 as a data destination. This way, the data can be transferred efficiently and securely without writing any code within the notebook. References:
Amazon SageMaker
AWS Data Pipeline

質問 # 29
A Machine Learning Specialist is developing a daily ETL workflow containing multiple ETL jobs The workflow consists of the following processes
* Start the workflow as soon as data is uploaded to Amazon S3
* When all the datasets are available in Amazon S3, start an ETL job to join the uploaded datasets with multiple terabyte-sized datasets already stored in Amazon S3
* Store the results of joining datasets in Amazon S3
* If one of the jobs fails, send a notification to the Administrator
Which configuration will meet these requirements?

A. Use AWS Lambda to chain other Lambda functions to read and join the datasets in Amazon S3 as soon as the data is uploaded to Amazon S3 Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure
B. Use AWS Lambda to trigger an AWS Step Functions workflow to wait for dataset uploads to complete in Amazon S3. Use AWS Glue to join the datasets Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure
C. Develop the ETL workflow using AWS Batch to trigger the start of ETL jobs when data is uploaded to Amazon S3 Use AWS Glue to join the datasets in Amazon S3 Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure
D. Develop the ETL workflow using AWS Lambda to start an Amazon SageMaker notebook instance Use a lifecycle configuration script to join the datasets and persist the results in Amazon S3 Use an Amazon CloudWatch alarm to send an SNS notification to the Administrator in the case of a failure

正解：B

質問 # 30
A Machine Learning Specialist uploads a dataset to an Amazon S3 bucket protected with server- side encryption using AWS KMS.
How should the ML Specialist define the Amazon SageMaker notebook instance so it can read the same dataset from Amazon S3?

A. Assign an IAM role to the Amazon SageMaker notebook with S3 read access to the dataset.
Grant permission in the KMS key policy to that role.
B. Assign the same KMS key used to encrypt data in Amazon S3 to the Amazon SageMaker notebook instance.
C. onfigure the Amazon SageMaker notebook instance to have access to the VPC. Grant permission in the KMS key policy to the notebook's KMS role.
D. Define security group(s) to allow all HTTP inbound/outbound traffic and assign those security group(s) to the Amazon SageMaker notebook instance.

正解：B

解説：
https://docs.aws.amazon.com/sagemaker/latest/dg/encryption-at-rest.html

質問 # 31
......

AmazonのMLS-C01の認証試験は現在IT業界でもっとも人気があって、その試験に合格すれば君の生活と仕事にいいです。 GoShikenはAmazonのMLS-C01「AWS Certified Machine Learning - Specialty」の認証試験の合格率を高めるのウエブサイトで、GoShiken中のIT業界の専門家が研究を通じてAmazonのMLS-C01の認証試験について問題集を研究し続けています。100%合格率は彼らの研究成果でございます。GoShikenを選られば、成功しましょう。

MLS-C01テスト内容: https://www.goshiken.com/Amazon/MLS-C01-mondaishu.html

無料でクラウドストレージから最新のGoShiken MLS-C01 PDFダンプをダウンロードする：https://drive.google.com/open?id=13SDzLXUhwdqfuN4gJYeRl1qViV6gtHWW