MLS-C01 技術内容 - Amazon MLS-C01 試験過去問 & AWS Certified Machine Learning Specialty - Omgzlook

AmazonのMLS-C01技術内容試験に参加する人はますます多くなっています。競争がこのように激しい情況で勝つためにどうしますか。ふさわしいアシスタントを選ぶのは一番重要なのです。 あなたに高品質で、全面的なMLS-C01技術内容参考資料を提供することは私たちの責任です。私たちより、MLS-C01技術内容試験を知る人はいません。 全力を尽くせば、MLS-C01技術内容試験の合格も可能となります。

AWS Certified Specialty MLS-C01 それをもって、試験は問題になりませんよ。

あるいは、無料で試験MLS-C01 - AWS Certified Machine Learning - Specialty技術内容問題集を更新してあげるのを選択することもできます。 Omgzlookはとても人気がありますから、それを選ばない理由はないです。もちろん、完璧なトレーニング資料を差し上げましたが、もしあなたに向いていないのなら無用になりますから、Omgzlookを利用する前に、一部の問題と解答を無料にダウンロードしてみることができます。

なぜ受験生のほとんどはOmgzlookを選んだのですか。それはOmgzlookがすごく便利で、広い通用性があるからです。OmgzlookのITエリートたちは彼らの専門的な目で、最新的なAmazonのMLS-C01技術内容試験トレーニング資料に注目していて、うちのAmazonのMLS-C01技術内容問題集の高い正確性を保証するのです。

Amazon MLS-C01技術内容 - 常々、時間とお金ばかり効果がないです。

OmgzlookのAmazonのMLS-C01技術内容試験トレーニング資料は受験生が模擬試験場で勉強させます。受験生は問題を選べ、テストの時間もコントロールできます。Omgzlookというサイトで、あなたはストレスと不安なく試験の準備をすることができますから、一般的な間違いを避けられます。そうしたら、あなたは自信を得ることができて、実際の試験で経験を活かして気楽に合格します。

できるだけ100%の通過率を保証使用にしています。Omgzlookは多くの受験生を助けて彼らにAmazonのMLS-C01技術内容試験に合格させることができるのは我々専門的なチームがAmazonのMLS-C01技術内容試験を研究して解答を詳しく分析しますから。

MLS-C01 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