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AWS Certified Specialty MLS-C01 できるだけ100％の通過率を保証使用にしています。

AWS Certified Specialty MLS-C01日本語版サンプル - AWS Certified Machine Learning - Specialty それで、「就職難」の場合には、他の人々と比べて、あなたはずっと優位に立つことができます。 ただ、社会に入るIT卒業生たちは自分能力の不足で、MLS-C01 テスト模擬問題集試験向けの仕事を探すのを悩んでいますか？それでは、弊社のAmazonのMLS-C01 テスト模擬問題集練習問題を選んで実用能力を速く高め、自分を充実させます。その結果、自信になる自己は面接のときに、面接官のいろいろな質問を気軽に回答できて、順調にMLS-C01 テスト模擬問題集向けの会社に入ります。

我々社のAmazon　MLS-C01日本語版サンプル問題集を購入するかどうかと疑問があると、弊社NewValidDumpsのMLS-C01日本語版サンプル問題集のサンプルをしてみるのもいいことです。試用した後、我々のMLS-C01日本語版サンプル問題集はあなたを試験に順調に合格させると信じられます。なぜと言うのは、我々社の専門家は改革に応じて問題の更新と改善を続けていくのは出発点から勝つからです。

また、Amazon MLS-C01日本語版サンプル問題集は的中率が高いです。

多分、MLS-C01日本語版サンプルテスト質問の数が伝統的な問題の数倍である。Amazon　MLS-C01日本語版サンプル試験参考書は全ての知識を含めて、全面的です。そして、MLS-C01日本語版サンプル試験参考書の問題は本当の試験問題とだいたい同じことであるとわかります。MLS-C01日本語版サンプル試験参考書があれば,ほかの試験参考書を勉強する必要がないです。

NewValidDumpsを選られば、成功しましょう。わずか数年の中に、Amazon MLS-C01日本語版サンプル認定試験がたくさんの人の日常生活にとても大きい影響を与えています。

MLS-C01 PDF DEMO:

QUESTION NO: 1
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: 2
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: 3
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: 4
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: 5
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

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Updated: May 28, 2022