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AWS Certified Specialty MLS-C01 早速買いに行きましょう。
OmgzlookのAmazonのMLS-C01 - AWS Certified Machine Learning - Specialty試験解説問題試験トレーニング資料は豊富な経験を持っているIT専門家が研究したものです。 一回だけでAmazonのMLS-C01 技術問題認定試験に合格したいか。Omgzlookは最も質の良いAmazonのMLS-C01 技術問題問題集を提供できるし、君の認定試験に合格するのに大変役に立ちます。
これも弊社が自信的にあなたに商品を薦める原因です。もし弊社のソフトを使ってあなたは残念で試験に失敗したら、弊社は全額で返金することを保証いたします。すべてのことの目的はあなたに安心に試験に準備さされるということです。
Amazon MLS-C01試験解説問題 - 試験に失敗したら、全額で返金する承諾があります。
AmazonのMLS-C01試験解説問題試験は大変です。あなたは復習資料に悩んでいるかもしれません。我々Omgzlookの提供するAmazonのMLS-C01試験解説問題ソフトを利用して自分の圧力を減少しましょう。我々のチームは複雑な問題集を整理するに通じて、毎年の試験の問題を分析して最高のAmazonのMLS-C01試験解説問題ソフトを作成します。今まで、我々は更新を努力しています。ご購入した後の一年間で、AmazonのMLS-C01試験解説問題試験が更新されたら、あなたを理解させます。
我々の提供するPDF版のAmazonのMLS-C01試験解説問題試験の資料はあなたにいつでもどこでも読めさせます。我々もオンライン版とソフト版を提供します。
MLS-C01 PDF DEMO:
QUESTION NO: 1
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: 2
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: 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 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
QUESTION NO: 5
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
OmgzlookはあなたのAmazonのScrum PAL-I試験を準備する間あなたの最もよい友達です。 我々OmgzlookはAmazonのAxis CTS試験問題集をリリースする以降、多くのお客様の好評を博したのは弊社にとって、大変な名誉なことです。 その他、我々のMicrosoft AI-900-CN日本語問題集を購入すると、英語版を送ります。 たとえば、ベストセラーのAmazon Amazon ANS-C01-JPN問題集は過去のデータを分析して作成ます。 Microsoft AI-900 - あるいは、他の科目の試験を変えていいです。
Updated: May 28, 2022