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模擬試験問題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模擬試験問題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。なぜ受験生のほとんどはOmgzlookを選んだのですか。 ご客様は弊社のMLS-C01模擬試験問題集問題集を購入するかどうかと判断する前に、我が社は無料に提供するサンプルをダウンロードして試すことができます。それで、不必要な損失を避けできます。 AmazonのMLS-C01模擬試験問題集認定試験に合格することはきっと君の職業生涯の輝い将来に大変役に立ちます。
私たちより、MLS-C01模擬試験問題集試験を知る人はいません。
我々MLS-C01 - AWS Certified Machine Learning - Specialty模擬試験問題集問題集の通過率は高いので、90％の合格率を保証します。 Omgzlookは多種なIT認証試験を受ける方を正確な資料を提供者でございます。弊社の無料なサンプルを遠慮なくダウンロードしてください。
Amazon MLS-C01模擬試験問題集試験認定書はIT職員野給料増加と仕事の昇進にとって、大切なものです。それで、我々社の無料のAmazon MLS-C01模擬試験問題集デモを参考して、あなたに相応しい問題集を入手します。暇の時間を利用して勉強します。
Amazon MLS-C01模擬試験問題集 - それに、あなたに極大な便利と快適をもたらせます。
我々は受験生の皆様により高いスピードを持っているかつ効率的なサービスを提供することにずっと力を尽くしていますから、あなたが貴重な時間を節約することに助けを差し上げます。Omgzlook AmazonのMLS-C01模擬試験問題集試験問題集はあなたに問題と解答に含まれている大量なテストガイドを提供しています。インターネットで時勢に遅れないMLS-C01模擬試験問題集勉強資料を提供するというサイトがあるかもしれませんが、Omgzlookはあなたに高品質かつ最新のAmazonのMLS-C01模擬試験問題集トレーニング資料を提供するユニークなサイトです。Omgzlookの勉強資料とAmazonのMLS-C01模擬試験問題集に関する指導を従えば、初めてAmazonのMLS-C01模擬試験問題集認定試験を受けるあなたでも一回で試験に合格することができます。
これはさまざまな試験の実践の検査に合格したもので、AmazonのMLS-C01模擬試験問題集認定試験に合格したかったら、Omgzlookを選ぶのは絶対正しいことです。AmazonのMLS-C01模擬試験問題集認定試験に受かる勉強サイトを探しているのなら、Omgzlookはあなたにとって一番良い選択です。
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