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AWS Certified Specialty MLS-C01 あなたの愛用する版をやってみよう。

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MLS-C01 PDF DEMO:

QUESTION NO: 1
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: 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 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

QUESTION NO: 4
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: 5
A Machine Learning Specialist built an image classification deep learning model. However the
Specialist ran into an overfitting problem in which the training and testing accuracies were 99% and
75%r respectively.
How should the Specialist address this issue and what is the reason behind it?
A. The learning rate should be increased because the optimization process was trapped at a local minimum.
B. The dimensionality of dense layer next to the flatten layer should be increased because the model is not complex enough.
C. The epoch number should be increased because the optimization process was terminated before it reached the global minimum.
D. The dropout rate at the flatten layer should be increased because the model is not generalized enough.
Answer: C

私たちより、IBM C1000-195試験を知る人はいません。 ShobhadoshiのAmazon Cloud Security Alliance CCSK-JPN問題集は専門家たちが数年間で過去のデータから分析して作成されて、試験にカバーする範囲は広くて、受験生の皆様のお金と時間を節約します。 CheckPoint 156-536 - 弊社の無料なサンプルを遠慮なくダウンロードしてください。 Amazon Amazon SAP-C02-JPN試験認定書はIT職員野給料増加と仕事の昇進にとって、大切なものです。 Fortinet FCSS_CDS_AR-7.6 - 君が選んだのはShobhadoshi、成功を選択したのに等しいです。

Updated: May 28, 2022

MLS-C01 過去問題 & Amazon AWS Certified Machine Learning Specialty テスト対策書

PDF問題と解答

試験コード:MLS-C01
試験名称:AWS Certified Machine Learning - Specialty
最近更新時間:2025-06-11
問題と解答:全 330
Amazon MLS-C01 最新関連参考書

  ダウンロード


 

模擬試験

試験コード:MLS-C01
試験名称:AWS Certified Machine Learning - Specialty
最近更新時間:2025-06-11
問題と解答:全 330
Amazon MLS-C01 参考資料

  ダウンロード


 

オンライン版

試験コード:MLS-C01
試験名称:AWS Certified Machine Learning - Specialty
最近更新時間:2025-06-11
問題と解答:全 330
Amazon MLS-C01 資格問題対応

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MLS-C01 模擬試験最新版

MLS-C01 日本語学習内容 関連認定
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