一番遠いところへ行った人はリスクを背負うことを恐れない人です。また、ShobhadoshiのAmazonのMLS-C01ファンデーション試験トレーニング資料が信頼できるのは多くの受験生に証明されたものです。ShobhadoshiのAmazonのMLS-C01ファンデーション試験トレーニング資料を利用したらきっと成功できますから、Shobhadoshiを選ばない理由はないです。 あなたにAmazon MLS-C01ファンデーション試験に関する最新かつ最完備の資料を勉強させ、試験に合格させることだと信じます。もしあなたはMLS-C01ファンデーション試験に合格しなかったら、全額返金のことを承諾します。 Shobhadoshiの問題集を利用してからこのすべてが真であることがわかります。
弊社のMLS-C01 - AWS Certified Machine Learning - Specialtyファンデーション試験問題集によって、あなたの心と精神の満足度を向上させながら、勉強した後MLS-C01 - AWS Certified Machine Learning - Specialtyファンデーション試験資格認定書を受け取って努力する人生はすばらしいことであると認識られます。 さて、はやく試験を申し込みましょう。Shobhadoshiはあなたを助けることができますから、心配する必要がないですよ。
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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 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: 3
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: 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
CompTIA PK0-005 - Shobhadoshiを利用したら、あなたはぜひ自信に満ちているようになり、これこそは試験の準備をするということを感じます。 AmazonのCheckPoint 156-536試験に合格することは容易なことではなくて、良い訓練ツールは成功の保証でShobhadoshiは君の試験の問題を準備してしまいました。 ServiceNow CIS-EM - 全てのIT人員がそんなにられるとしたら、国はぜひ強くなります。 ITの専門者はAmazonのGoogle Professional-Cloud-Database-Engineer認定試験があなたの願望を助けって実現できるのがよく分かります。 SAP C-S4CPB-2502 - この資料はインターネットでのクリック率と好評率が一番高いです。
Updated: May 28, 2022
試験コード:MLS-C01
試験名称:AWS Certified Machine Learning - Specialty
最近更新時間:2025-06-07
問題と解答:全 324 問
Amazon MLS-C01 模擬対策問題
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試験コード:MLS-C01
試験名称:AWS Certified Machine Learning - Specialty
最近更新時間:2025-06-07
問題と解答:全 324 問
Amazon MLS-C01 問題数
ダウンロード
試験コード:MLS-C01
試験名称:AWS Certified Machine Learning - Specialty
最近更新時間:2025-06-07
問題と解答:全 324 問
Amazon MLS-C01 最新関連参考書
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