我々のAmazonのAWS-Certified-Machine-Learning-Specialty基礎訓練ソフトはあなたのすべての需要を満たすのを希望します。問題集の全面性と権威性、AmazonのAWS-Certified-Machine-Learning-Specialty基礎訓練ソフトがPDF版、オンライン版とソフト版があるという資料のバーションの多様性、購入の前にデモの無料ダウンロード、購入の後でAmazonのAWS-Certified-Machine-Learning-Specialty基礎訓練ソフトの一年間の無料更新、これ全部は我々の誠の心を示しています。 最新の資源と最新の動態が第一時間にお客様に知らせいたします。何の問題があったらお気軽に聞いてください。 AmazonのAWS-Certified-Machine-Learning-Specialty基礎訓練試験に合格しがたいですが、我々Goldmile-Infobizの提供するAmazonのAWS-Certified-Machine-Learning-Specialty基礎訓練試験の資料を通して多くの人は試験に合格しました。
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では、躊躇しなくて、Amazon AWS-Certified-Machine-Learning-Specialty基礎訓練認定試験の問題集を早く購入しましょう！あなたはIT業界の玄人になりたいですか？ここでAmazon AWS-Certified-Machine-Learning-Specialty基礎訓練認定試験の問題集をお勧めます。AWS-Certified-Machine-Learning-Specialty基礎訓練認定試験の問題集は大勢の人の注目を集め、とても人気がある商品です。
Amazon AWS-Certified-Machine-Learning-Specialty基礎訓練 - 君の初めての合格を目標にします。
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多くの人々は高い難度のIT認証試験に合格するのは専門の知識が必要だと思います。それは確かにそうですが、その知識を身につけることは難しくないとといわれています。
AWS-Certified-Machine-Learning-Specialty 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
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