MLS-C01 日本語解説集、 Amazon MLS-C01 認証試験 & AWS Certified Machine Learning Specialty - Omgzlook

あなたに高品質で、全面的なMLS-C01日本語解説集参考資料を提供することは私たちの責任です。私たちより、MLS-C01日本語解説集試験を知る人はいません。あなたはMLS-C01日本語解説集試験に不安を持っていますか?MLS-C01日本語解説集参考資料をご覧下さい。 世界の激しい変化によって、MLS-C01日本語解説集試験の内容も変わっています。でも、弊社のMLS-C01日本語解説集試験参考書は古くなることを心配する必要がないです。 Omgzlookはきみの貴重な時間を節約するだけでなく、 安心で順調に試験に合格するのを保証します。

AWS Certified Specialty MLS-C01 Omgzlookには専門的なエリート団体があります。

AWS Certified Specialty MLS-C01日本語解説集 - AWS Certified Machine Learning - Specialty あなたが決して後悔しないことを保証します。 OmgzlookのAmazonのMLS-C01 復習攻略問題試験トレーニング資料を手に入れたら、我々は一年間の無料更新サービスを提供します。それはあなたがいつでも最新の試験資料を持てるということです。

弊社のAmazonのMLS-C01日本語解説集勉強資料を利用したら、きっと試験を受けるための時間とお金を節約できます。OmgzlookのAmazonのMLS-C01日本語解説集問題集を買う前に、一部の問題と解答を無料にダウンロードすることができます。PDFのバージョンとソフトウェアのバージョンがありますから、ソフトウェアのバージョンを必要としたら、弊社のカスタマーサービススタッフから取得してください。

Amazon MLS-C01日本語解説集 - そうしたら速くOmgzlookを選びましょう。

なぜ受験生のほとんどはOmgzlookを選んだのですか。それはOmgzlookがすごく便利で、広い通用性があるからです。OmgzlookのITエリートたちは彼らの専門的な目で、最新的なAmazonのMLS-C01日本語解説集試験トレーニング資料に注目していて、うちのAmazonのMLS-C01日本語解説集問題集の高い正確性を保証するのです。もし君はいささかな心配することがあるなら、あなたはうちの商品を購入する前に、Omgzlookは無料でサンプルを提供することができます。

OmgzlookのAmazonのMLS-C01日本語解説集試験トレーニング資料は特別に受験生を対象として研究されたものです。インターネットでこんな高品質の資料を提供するサイトはOmgzlookしかないです。

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