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MLS-C01 受験準備、 Amazon MLS-C01 全真問題集 & AWS Certified Machine Learning Specialty - Royalholidayclubbed
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最もよくて最新で資料を提供いたします。こうして、君は安心で試験の準備を行ってください。弊社の資料を使って、１００％に合格を保証いたします。 AmazonのMLS-C01受験準備試験はいくつ難しくても文句を言わないで、我々Royalholidayclubbedの提供する資料を通して、あなたはAmazonのMLS-C01受験準備試験に合格することができます。AmazonのMLS-C01受験準備試験を準備しているあなたに試験に合格させるために、我々Royalholidayclubbedは模擬試験ソフトを更新し続けています。 多くのAmazonのMLS-C01受験準備認定試験を準備している受験生がいろいろなMLS-C01受験準備「AWS Certified Machine Learning - Specialty」認証試験についてサービスを提供するサイトオンラインがみつけたがRoyalholidayclubbedはIT業界トップの専門家が研究した参考材料で権威性が高く、品質の高い教育資料で、一回に参加する受験者も合格するのを確保いたします。
AWS Certified Specialty MLS-C01 弊社の商品が好きなのは弊社のたのしいです。
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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
Huawei H20-695_V2.0 - 君がうちの学習教材を購入した後、私たちは一年間で無料更新サービスを提供することができます。 あるいは、無料で試験Amazon CLF-C02問題集を更新してあげるのを選択することもできます。 Fortinet FCSS_NST_SE-7.4 - これも弊社が自信的にあなたに商品を薦める原因です。 CompTIA PT0-003 - なぜ受験生のほとんどはRoyalholidayclubbedを選んだのですか。 しかし、我々はAmazonのJuniper JN0-363試験のソフトウェアは、あなたの期待に応えると信じて、私はあなたの成功を祈っています！
Updated: May 28, 2022
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