もしGoldmile-Infobizの学習教材を購入した後、どんな問題があれば、或いは試験に不合格になる場合は、私たちが全額返金することを保証いたします。Goldmile-Infobizを信じて、私たちは君のそばにいるから。Goldmile-Infobizの AmazonのMLS-C01模擬解説集試験トレーニング資料はGoldmile-Infobizの実力と豊富な経験を持っているIT専門家が研究したもので、本物のAmazonのMLS-C01模擬解説集試験問題とほぼ同じです。 そして、試験を安心に参加してください。IT業界の中でたくさんの野心的な専門家がいって、IT業界の中でより一層頂上まで一歩更に近く立ちたくてAmazonのMLS-C01模擬解説集試験に参加して認可を得たくて、Amazon のMLS-C01模擬解説集試験が難度の高いので合格率も比較的低いです。 あなたはどのような方式で試験を準備するのが好きですか。
AWS Certified Specialty MLS-C01 このサービスは無料なのです。
AWS Certified Specialty MLS-C01模擬解説集 - AWS Certified Machine Learning - Specialty それはあなたが成功認定を助ける良いヘルパーですから、あなたはまだ何を待っているのですか。 これなので、今から我々社Goldmile-InfobizのMLS-C01 対応資料試験に合格するのに努力していきます。弊社のAmazonのMLS-C01 対応資料真題によって、資格認定証明書を受け取れて、仕事の昇進を実現できます。
AmazonのMLS-C01模擬解説集認定試験に受かるためにがんばって勉強していれば、Goldmile-Infobizはあなたにヘルプを与えます。Goldmile-Infobiz が提供したAmazonのMLS-C01模擬解説集問題集は実践の検査に合格したもので、最も良い品質であなたがAmazonのMLS-C01模擬解説集認定試験に合格することを保証します。
Amazon MLS-C01模擬解説集 - 逆境は人をテストすることができます。
IT業界で働いている多くの人はAmazonのMLS-C01模擬解説集試験の準備が大変だと知っています。我々Goldmile-InfobizはMLS-C01模擬解説集試験の難しさを減らないとは言え、試験準備の難しさを減ることができます。我々の提供する問題集を体験してから、あなたはAmazonのMLS-C01模擬解説集試験に合格できる自信を持っています。
自分のレベルを高めたいですか。では、仕事に役に立つスキルをもっと身に付けましょう。
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 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: 4
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: 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