我々はAmazonのMLS-C01資格準備試験のソフトだけでなく、各方面のアフターサービスの上で尽力します。成功の喜びは大きいです。我々は弊社のソフトを通してあなたにAmazonのMLS-C01資格準備試験に合格する喜びを感じさせると希望しています。 成功の楽園にどうやって行きますか。ショートカットは一つしかないです。 ほかのたくさんの受験生は生活の中でのことに挑戦しています。
AWS Certified Specialty MLS-C01 自分の幸せは自分で作るものだと思われます。
AWS Certified Specialty MLS-C01資格準備 - AWS Certified Machine Learning - Specialty しかも、Goldmile-Infobizは当面の市場で皆さんが一番信頼できるサイトです。 もしあなたはAmazonのMLS-C01 日本語対策問題集試験に準備しているなら、弊社Goldmile-InfobizのMLS-C01 日本語対策問題集問題集を使ってください。現在、多くの外資系会社はAmazonのMLS-C01 日本語対策問題集試験認定を持つ職員に奨励を与えます。
Goldmile-InfobizのAmazonのMLS-C01資格準備試験トレーニング資料は正確性が高くて、カバー率も広い。あなたがAmazonのMLS-C01資格準備認定試験に合格するのに最も良くて、最も必要な学習教材です。うちのAmazonのMLS-C01資格準備問題集を購入したら、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。
Amazon MLS-C01資格準備 - ふさわしい方式を選ぶのは一番重要なのです。
弊社のMLS-C01資格準備問題集のメリットはいろいろな面で記述できます。価格はちょっと高いですが、MLS-C01資格準備試験に最も有効な参考書です。MLS-C01資格準備問題集は便利で、どこでもいつでも勉強できます。また、時間を節約でき、短い時間で勉強したら、MLS-C01資格準備試験に参加できます。
あなたが我々の資料を購入するとき、あなたのAmazonのMLS-C01資格準備試験に関するすべてのヘルプを購入しました。世界は変化している、我々はできるだけそのペースを維持する必要があります。
MLS-C01 PDF DEMO:
QUESTION NO: 1
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: 2
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: 3
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: 4
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
QUESTION NO: 5
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
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Updated: May 28, 2022