我們Goldmile-Infobiz Amazon的MLS-C01考題資源考試培訓資料是最佳的培訓資料，如果你是IT人員，它將是你必選的培訓資料，不要拿你的未來來賭明天，Goldmile-Infobiz Amazon的MLS-C01考題資源考試培訓資料絕對值得信賴，我們是專門給全世界的IT認證的考生提供培訓資料的，包括試題及答案，實現 Amazon的MLS-C01考題資源考試認證，是許多IT和網路專業人士的目標，Goldmile-Infobiz的合格率是難以置信的高，在Goldmile-Infobiz，我們致力於你不斷的取得成功。 這個資料的價值等同於其他一切的與考試相關的參考書。這種說法並不誇張。 於是，IT行業的競爭愈發激烈了。
AWS Certified Specialty MLS-C01 如果你想輕鬆通過考試，那麼快來試試吧。
如果你不想因為考試浪費太多的時間與精力，那麼Goldmile-Infobiz的MLS-C01 - AWS Certified Machine Learning - Specialty考題資源考古題無疑是你最好的選擇。 另外，如果你實在沒有準備考試的時間，那麼你只需要記好這個考古題裏的試題和答案。因為這個考古題包括了真實考試中的所有試題，所以只是這樣你也可以通過考試。
Goldmile-Infobiz以它強大的考古題得到人們的認可，只要你選擇它作為你的考前復習工具，就會在MLS-C01考題資源資格考試中有非常滿意的收穫，這也是大家有目共睹的。現在馬上去網站下載免費試用版本，你就會相信自己的選擇不會錯。Goldmile-Infobiz網站在通過MLS-C01考題資源資格認證考試的考生中有著良好的口碑。
而且通過 Amazon Amazon MLS-C01考題資源 認證考試也不是很簡單的。
Goldmile-Infobiz是個可以為所有有關於IT認證考試提供資料的網站。Goldmile-Infobiz可以為你提供最好最新的考試資源。選擇Goldmile-Infobiz你可以安心的準備你的Amazon MLS-C01考題資源考試。我們的培訓才料可以保證你100%的通過Amazon MLS-C01考題資源認證考試，如果沒有通過我們將全額退款並且會迅速的更新考試練習題和答案，但這幾乎是不可能發生的。Goldmile-Infobiz可以為你通過Amazon MLS-C01考題資源的認證考試提供幫助，也可以為你以後的工作提供幫助。雖然有很多方法可以幫你達到你的這些目的，但是選擇Goldmile-Infobiz是你最明智的選擇，Goldmile-Infobiz可以使你花時間更短金錢更少並且更有把握地通過考試，而且我們還會為你提供一年的免費售後服務。
為了通過Amazon MLS-C01考題資源 認證考試，請選擇我們的Goldmile-Infobiz來取得好的成績。你不會後悔這樣做的，花很少的錢取得如此大的成果這是值得的。
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