ほかの人はあちこちAmazonのAWS-Certified-Machine-Learning-Specialty更新版試験の資料を探しているとき、あなたは問題集の勉強を始めました。準備の段階であなたはリーダーしています。我々Goldmile-Infobizの提供するAmazonのAWS-Certified-Machine-Learning-Specialty更新版試験のソフトは豊富な試験に関する資源を含めてあなたに最も真実のAmazonのAWS-Certified-Machine-Learning-Specialty更新版試験環境で体験させます。 Amazon AWS-Certified-Machine-Learning-Specialty更新版資格認定はIT技術領域に従事する人に必要があります。我々社のAmazon AWS-Certified-Machine-Learning-Specialty更新版試験練習問題はあなたに試験うま合格できるのを支援します。 だから、大人気なIT仕事に従事したいあなたは今から準備して努力するのではないでしょうか？さあ、ここで我々社のAmazonのAWS-Certified-Machine-Learning-Specialty更新版試験模擬問題を推薦させてくださいませんか。
AWS Certified Machine Learning AWS-Certified-Machine-Learning-Specialty でも大丈夫です。
AWS Certified Machine Learning AWS-Certified-Machine-Learning-Specialty更新版 - AWS Certified Machine Learning - Specialty いまの市場にとてもよい問題集が探すことは難しいです。 この問題集には実際の試験に出る可能性のあるすべての問題が含まれています。従って、この問題集を真面目に学ぶ限り、AWS-Certified-Machine-Learning-Specialty 資格受験料認定試験に合格するのは難しいことではありません。
Goldmile-Infobizで、あなたは一番良い準備資料を見つけられます。その資料は練習問題と解答に含まれています。弊社の資料があなたに練習を実践に移すチャンスを差し上げ、あなたはぜひAmazonのAWS-Certified-Machine-Learning-Specialty更新版試験に合格して自分の目標を達成できます。
Amazon AWS-Certified-Machine-Learning-Specialty更新版 - 自分がやっていることに満足していますか。
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実際にはそれは全く不要です。IT認定試験はあなたの思い通りに神秘的なものではありません。
AWS-Certified-Machine-Learning-Specialty 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