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AWS Certified Machine Learning AWS-Certified-Machine-Learning-Specialty 我々の誠意を信じてください。
あなたは各バーションのAmazonのAWS-Certified-Machine-Learning-Specialty - AWS Certified Machine Learning - Specialty試験概要試験の資料をダウンロードしてみることができ、あなたに一番ふさわしいバーションを見つけることができます。 自分のIT業界での発展を希望したら、AmazonのAWS-Certified-Machine-Learning-Specialty 試験攻略試験に合格する必要があります。AmazonのAWS-Certified-Machine-Learning-Specialty 試験攻略試験はいくつ難しくても文句を言わないで、我々Omgzlookの提供する資料を通して、あなたはAmazonのAWS-Certified-Machine-Learning-Specialty 試験攻略試験に合格することができます。
このインタネット時代において、AmazonのAWS-Certified-Machine-Learning-Specialty試験概要資格証明書を持つのは羨ましいことで、インテリとしての印です。どこからAWS-Certified-Machine-Learning-Specialty試験概要試験の優秀な資料を探すできるか？では、我々社OmgzlookのAWS-Certified-Machine-Learning-Specialty試験概要問題集を選んでみてくださいませんか。この小さい試すアクションはあなたが今までの最善のオプションであるかもしれません。
Amazon AWS-Certified-Machine-Learning-Specialty試験概要 - お客様の満足は我々の進む力です。
人によって目標が違いますが、あなたにAmazon AWS-Certified-Machine-Learning-Specialty試験概要試験に順調に合格できるのは我々の共同の目標です。この目標の達成はあなたがIT技術領域へ行く更なる発展の一歩ですけど、我々社Omgzlook存在するこそすべての意義です。だから、我々社は力の限りで弊社のAmazon AWS-Certified-Machine-Learning-Specialty試験概要試験資料を改善し、改革の変更に応じて更新します。あなたはいつまでも最新版の問題集を使用できるために、ご購入の一年間で無料の更新を提供します。
でも、どのようにAWS-Certified-Machine-Learning-Specialty試験概要認定試験に合格しますか？もちろん、AWS-Certified-Machine-Learning-Specialty試験概要問題集を選ぶべきです。選ぶ理由はなんですか？お客様にAWS-Certified-Machine-Learning-Specialty試験概要認定試験資料を提供してあげ、勉強時間は短くても、合格できることを保証いたします。
AWS-Certified-Machine-Learning-Specialty PDF DEMO:
QUESTION NO: 1
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: 2
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
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 working for an online fashion company wants to build a data ingestion solution for the company's Amazon S3-based data lake.
The Specialist wants to create a set of ingestion mechanisms that will enable future capabilities comprised of:
* Real-time analytics
* Interactive analytics of historical data
* Clickstream analytics
* Product recommendations
Which services should the Specialist use?
A. Amazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data
Analytics for historical data insights; Amazon DynamoDB streams for clickstream analytics; AWS Glue to generate personalized product recommendations
B. AWS Glue as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for historical data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations
C. AWS Glue as the data dialog; Amazon Kinesis Data Streams and Amazon Kinesis Data Analytics for real-time data insights; Amazon Kinesis Data Firehose for delivery to Amazon ES for clickstream analytics; Amazon EMR to generate personalized product recommendations
D. Amazon Athena as the data catalog; Amazon Kinesis Data Streams and Amazon Kinesis Data
Analytics for near-realtime data insights; Amazon Kinesis Data Firehose for clickstream analytics; AWS
Glue to generate personalized product recommendations
Answer: C
QUESTION NO: 5
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
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Updated: May 28, 2022