MLS-C01 日本語資格取得 & Amazon AWS Certified Machine Learning Specialty 日本語認定 - Omgzlook

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AWS Certified Specialty MLS-C01 我々の誠意を信じてください。

AWS Certified Specialty MLS-C01日本語資格取得 - AWS Certified Machine Learning - Specialty それに、問題集の合格率が100パーセントに達するのですから、あなたは安心に試験を受けることができます。 自分のIT業界での発展を希望したら、AmazonのMLS-C01 難易度受験料試験に合格する必要があります。AmazonのMLS-C01 難易度受験料試験はいくつ難しくても文句を言わないで、我々Omgzlookの提供する資料を通して、あなたはAmazonのMLS-C01 難易度受験料試験に合格することができます。

そこで、IT業界で働く人も多くなっています。このように、IT業界の競争が一層激しくなります。同様にIT業界で働いていて、IT夢を持っているあなたは、きっと他の人にキャッチアップされ、追い抜かれることを望まないでしょう。

Amazon MLS-C01日本語資格取得 - 早くOmgzlookの問題集を君の手に入れましょう。

我々Omgzlookが自分のソフトに自信を持つのは我々のAmazonのMLS-C01日本語資格取得ソフトでAmazonのMLS-C01日本語資格取得試験に参加する皆様は良い成績を取りましたから。AmazonのMLS-C01日本語資格取得試験に合格して彼らのよりよい仕事を探せるチャンスは多くなります。あなたに安心させるために、我々のソフトを利用してあなたが試験に失敗したら、我々は全額で返金するのを承諾してよりよいAmazonのMLS-C01日本語資格取得ソフトを開発し続けます。

君が後悔しないようにもっと少ないお金を使って大きな良い成果を取得するためにOmgzlookを選択してください。Omgzlookはまた一年間に無料なサービスを更新いたします。

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 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: 3
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: 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