MLS-C01最新考古題，MLS-C01考試心得 - Amazon MLS-C01考題寶典 - Royalholidayclubbed

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Amazon MLS-C01最新考古題就是一個相當有難度的認證考試，雖然很多人報名參加Amazon MLS-C01最新考古題考試，但是通過率並不是很高。在這個資訊時代，IT行業被很多人關注，但是在如今人才濟濟的社會裏任然比較缺乏IT人。很多公司都招聘IT人才，他們一般考察IT人才的能力會參考他們擁有的IT相關認證證書，所以擁有一些IT相關的認證證書是受很多公司歡迎的。如果你對Royalholidayclubbed感興趣，你可以先在網上免費下載Royalholidayclubbed提供的部分關於Amazon MLS-C01最新考古題 認證考試的練習題和答案作為嘗試。Amazon MLS-C01最新考古題 認證證書是很多IT人士夢寐以求的。 Royalholidayclubbed最近研究出來了關於熱門的Amazon MLS-C01最新考古題 認證考試的培訓方案，包括一些針對性的測試題，可以幫助你鞏固知識，讓你為Amazon MLS-C01最新考古題 認證考試做好充分的準備。

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Royalholidayclubbed為通過MLS-C01 - AWS Certified Machine Learning - Specialty最新考古題考試提供最完整有效的方案，幫祝廣大考生在考試中獲得更多的優勢。已經報名參加考試的你，現在正在煩惱應該怎麼準備考試嗎？如果是這樣的話，請看下面的內容，我現在告訴你通過MLS-C01 最新考證考試的捷徑。可以讓你一次就通過考試的優秀的MLS-C01 最新考證考試資料出現了。

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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
Amazon Connect has recently been tolled out across a company as a contact call center The solution has been configured to store voice call recordings on Amazon S3 The content of the voice calls are being analyzed for the incidents being discussed by the call operators Amazon Transcribe is being used to convert the audio to text, and the output is stored on Amazon S3 Which approach will provide the information required for further analysis?
A. Use Amazon Comprehend with the transcribed files to build the key topics
B. Use the AWS Deep Learning AMI with Gluon Semantic Segmentation on the transcribed files to train and build a model for the key topics
C. Use Amazon Translate with the transcribed files to train and build a model for the key topics
D. Use the Amazon SageMaker k-Nearest-Neighbors (kNN) algorithm on the transcribed files to generate a word embeddings dictionary for the key topics
Answer: C

QUESTION NO: 5
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

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Updated: May 28, 2022

by RHC.

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