現在IT技術会社に通勤しているあなたは、AmazonのMLS-C01難易度受験料試験認定を取得しましたか?MLS-C01難易度受験料試験認定は給料の増加とジョブのプロモーションに役立ちます。短時間でMLS-C01難易度受験料試験に一発合格したいなら、我々社のAmazonのMLS-C01難易度受験料資料を参考しましょう。また、MLS-C01難易度受験料問題集に疑問があると、メールで問い合わせてください。 彼らにAmazonのMLS-C01難易度受験料試験に合格させました。弊社のホームページでソフトのデモをダウンロードして利用してみます。 あなたの資料を探す時間を節約し、Amazon MLS-C01難易度受験料試験の復習をやっています。
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それに、AmazonのMLS-C01 - AWS Certified Machine Learning - Specialty難易度受験料の試験の実践経験やテストダンプにも含まれています。 AmazonのMLS-C01 絶対合格のオンラインサービスのスタディガイドを買いたかったら、Goldmile-Infobizを買うのを薦めています。Goldmile-Infobizは同じ作用がある多くのサイトでリーダーとしているサイトで、最も良い品質と最新のトレーニング資料を提供しています。
Goldmile-InfobizのAmazonのMLS-C01難易度受験料問題集を買う前に、一部の問題と解答を無料に試用することができます。そうすると、Goldmile-InfobizのAmazonのMLS-C01難易度受験料トレーニング資料の品質をよく知っています。Goldmile-InfobizのAmazonのMLS-C01難易度受験料問題集は絶対あなたの最良の選択です。
Amazon MLS-C01難易度受験料 - 今教えてあげますよ。
AmazonのMLS-C01難易度受験料試験に関する権威のある学習教材を見つけないで、悩んでいますか?世界中での各地の人々はほとんどAmazonのMLS-C01難易度受験料試験を受験しています。AmazonのMLS-C01難易度受験料の認証試験の高品質の資料を提供しているユニークなサイトはGoldmile-Infobizです。もし君はまだ心配することがあったら、私たちのAmazonのMLS-C01難易度受験料問題集を購入する前に、一部分のフリーな試験問題と解答をダンロードして、試用してみることができます。
AmazonのMLS-C01難易度受験料認定試験を受験する気があるのですか。この試験を受けた身の回りの人がきっと多くいるでしょう。
MLS-C01 PDF DEMO:
QUESTION NO: 1
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: 2
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: 3
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: 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
A Machine Learning Specialist has created a deep learning neural network model that performs well on the training data but performs poorly on the test data.
Which of the following methods should the Specialist consider using to correct this? (Select THREE.)
A. Decrease dropout.
B. Increase regularization.
C. Increase feature combinations.
D. Decrease feature combinations.
E. Decrease regularization.
F. Increase dropout.
Answer: A,B,C
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Updated: May 28, 2022