MLS-C01 専門知識 & Amazon AWS Certified Machine Learning Specialty テスト模擬問題集 - Royalholidayclubbed

 

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Royalholidayclubbed を選択して100%の合格率を確保することができて、もし試験に失敗したら、Royalholidayclubbedが全額で返金いたします。 それで、IT人材として毎日自分を充実して、MLS-C01専門知識問題集を学ぶ必要があります。弊社のMLS-C01専門知識問題集はあなたにこのチャンスを全面的に与えられます。 そうしたらあなたはRoyalholidayclubbedが用意した問題集にもっと自信があります。

Amazon MLS-C01専門知識試験を目前に控えて、不安なのですか。

AWS Certified Specialty MLS-C01専門知識 - AWS Certified Machine Learning - Specialty もっと長い時間をもらって試験を準備したいのなら、あなたがいつでもサブスクリプションの期間を伸びることができます。 人生は自転車に乗ると似ていて、やめない限り、倒れないから。IT技術職員として、周りの人はAmazon MLS-C01 受験方法試験に合格し高い月給を持って、上司からご格別の愛護を賜り更なるジョブプロモーションを期待されますけど、あんたはこういうように所有したいますか。

認証専門家や技術者及び全面的な言語天才がずっと最新のAmazonのMLS-C01専門知識試験を研究していますから、AmazonのMLS-C01専門知識認定試験に受かりたかったら、Royalholidayclubbedのサイトをクッリクしてください。あなたに成功に近づいて、夢の楽園に一歩一歩進めさせられます。Royalholidayclubbed AmazonのMLS-C01専門知識試験トレーニング資料というのは一体なんでしょうか。

Amazon MLS-C01専門知識 - そして、試験を安心に参加してください。

常々、時間とお金ばかり効果がないです。正しい方法は大切です。我々Royalholidayclubbedは一番効果的な方法を探してあなたにAmazonのMLS-C01専門知識試験に合格させます。弊社のAmazonのMLS-C01専門知識ソフトを購入するのを決めるとき、我々は各方面であなたに保障を提供します。購入した前の無料の試み、購入するときのお支払いへの保障、購入した一年間の無料更新AmazonのMLS-C01専門知識試験に失敗した全額での返金…これらは我々のお客様への承諾です。

弊社のMLS-C01専門知識のトレーニング資料を買ったら、一年間の無料更新サービスを差し上げます。もっと長い時間をもらって試験を準備したいのなら、あなたがいつでもサブスクリプションの期間を伸びることができます。

MLS-C01 PDF DEMO:

QUESTION NO: 1
Amazon Connect has recently been tolled out across a company as a contact call center The solution has been configured to store voice call recordings on Amazon S3 The content of the voice calls are being analyzed for the incidents being discussed by the call operators Amazon Transcribe is being used to convert the audio to text, and the output is stored on Amazon S3 Which approach will provide the information required for further analysis?
A. Use Amazon Comprehend with the transcribed files to build the key topics
B. Use the AWS Deep Learning AMI with Gluon Semantic Segmentation on the transcribed files to train and build a model for the key topics
C. Use Amazon Translate with the transcribed files to train and build a model for the key topics
D. Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the transcribed files to generate a word embeddings dictionary for the key topics
Answer: C

QUESTION NO: 2
A Data Scientist wants to gain real-time insights into a data stream of GZIP files. Which solution would allow the use of SQL to query the stream with the LEAST latency?
A. Amazon Kinesis Data Firehose to transform the data and put it into an Amazon S3 bucket.
B. Amazon Kinesis Data Analytics with an AWS Lambda function to transform the data.
C. AWS Glue with a custom ETL script to transform the data.
D. An Amazon Kinesis Client Library to transform the data and save it to an Amazon ES cluster.
Answer: B

QUESTION NO: 3
A Machine Learning Specialist is using Amazon SageMaker to host a model for a highly available customer-facing application .
The Specialist has trained a new version of the model, validated it with historical data, and now wants to deploy it to production To limit any risk of a negative customer experience, the Specialist wants to be able to monitor the model and roll it back, if needed What is the SIMPLEST approach with the LEAST risk to deploy the model and roll it back, if needed?
A. Create a SageMaker endpoint and configuration for the new model version. Redirect production traffic to the new endpoint by using a load balancer Revert traffic to the last version if the model does not perform as expected.
B. Update the existing SageMaker endpoint to use a new configuration that is weighted to send 5% of the traffic to the new variant. Revert traffic to the last version by resetting the weights if the model does not perform as expected.
C. Update the existing SageMaker endpoint to use a new configuration that is weighted to send 100% of the traffic to the new variant Revert traffic to the last version by resetting the weights if the model does not perform as expected.
D. Create a SageMaker endpoint and configuration for the new model version. Redirect production traffic to the new endpoint by updating the client configuration. Revert traffic to the last version if the model does not perform as expected.
Answer: D

QUESTION NO: 4
A Machine Learning Specialist receives customer data for an online shopping website. The data includes demographics, past visits, and locality information. The Specialist must develop a machine learning approach to identify the customer shopping patterns, preferences and trends to enhance the website for better service and smart recommendations.
Which solution should the Specialist recommend?
A. A neural network with a minimum of three layers and random initial weights to identify patterns in the customer database
B. Random Cut Forest (RCF) over random subsamples to identify patterns in the customer database
C. Latent Dirichlet Allocation (LDA) for the given collection of discrete data to identify patterns in the customer database.
D. Collaborative filtering based on user interactions and correlations to identify patterns in the customer database
Answer: D

QUESTION NO: 5
A Machine Learning Specialist kicks off a hyperparameter tuning job for a tree-based ensemble model using Amazon SageMaker with Area Under the ROC Curve (AUC) as the objective metric This workflow will eventually be deployed in a pipeline that retrains and tunes hyperparameters each night to model click-through on data that goes stale every 24 hours With the goal of decreasing the amount of time it takes to train these models, and ultimately to decrease costs, the Specialist wants to reconfigure the input hyperparameter range(s) Which visualization will accomplish this?
A. A scatter plot with points colored by target variable that uses (-Distributed Stochastic Neighbor
Embedding (I-SNE) to visualize the large number of input variables in an easier-to-read dimension.
B. A scatter plot showing (he performance of the objective metric over each training iteration
C. A histogram showing whether the most important input feature is Gaussian.
D. A scatter plot showing the correlation between maximum tree depth and the objective metric.
Answer: A

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Updated: May 28, 2022

 

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