Shobhadoshiで、あなたの試験のためのテクニックと勉強資料を見つけることができます。ShobhadoshiのAmazonのMLS-C01試験準備試験トレーニング資料は豊富な知識と経験を持っているIT専門家に研究された成果で、正確度がとても高いです。Shobhadoshiに会ったら、最高のトレーニング資料を見つけました。 真剣にShobhadoshiのAmazon MLS-C01試験準備問題集を勉強する限り、受験したい試験に楽に合格することができるということです。IT認定試験の中でどんな試験を受けても、ShobhadoshiのMLS-C01試験準備試験参考資料はあなたに大きなヘルプを与えることができます。 ShobhadoshiはIT認定試験を受験した多くの人々を助けました。

AWS Certified Specialty MLS-C01 ここには、私たちは君の需要に応じます。

AWS Certified Specialty MLS-C01試験準備 - AWS Certified Machine Learning - Specialty Shobhadoshiを選ぶなら、絶対に後悔させません。 ShobhadoshiのAmazonのMLS-C01 認定デベロッパー試験トレーニング資料は試験問題と解答を含まれて、豊富な経験を持っているIT業種の専門家が長年の研究を通じて作成したものです。その権威性は言うまでもありません。

私たちは最も新しくて、最も正確性の高いAmazonのMLS-C01試験準備試験トレーニング資料を提供します。長年の努力を通じて、ShobhadoshiのAmazonのMLS-C01試験準備認定試験の合格率が１００パーセントになっていました。もし君はいささかな心配することがあるなら、あなたはうちの商品を購入する前に、Shobhadoshiは無料でサンプルを提供することができます。

Amazon MLS-C01試験準備 - 弊社の商品が好きなのは弊社のたのしいです。

周りの多くの人は全部Amazon　MLS-C01試験準備資格認定試験にパースしまして、彼らはどのようにできましたか。今には、あなたにShobhadoshiを教えさせていただけませんか。我々社サイトのAmazon　MLS-C01試験準備問題庫は最新かつ最完備な勉強資料を有して、あなたに高品質のサービスを提供するのはMLS-C01試験準備資格認定試験の成功にとって唯一の選択です。躊躇わなくて、Shobhadoshiサイト情報を早く了解して、あなたに試験合格を助かってあげますようにお願いいたします。

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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 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: 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