うちのAmazonのMLS-C01試験過去問問題集を購入したら、私たちは一年間で無料更新サービスを提供することができます。もし学習教材は問題があれば、或いは試験に不合格になる場合は、全額返金することを保証いたします。Goldmile-InfobizのAmazonのMLS-C01試験過去問試験トレーニング資料は正確性が高くて、カバー率も広い。 こんな保障がありますから、心配する必要は全然ないですよ。Goldmile-InfobizのMLS-C01試験過去問問題集は多くの受験生に検証されたものですから、高い成功率を保証できます。 Goldmile-Infobizの AmazonのMLS-C01試験過去問試験トレーニング資料はGoldmile-Infobizの実力と豊富な経験を持っているIT専門家が研究したもので、本物のAmazonのMLS-C01試験過去問試験問題とほぼ同じです。
AWS Certified Specialty MLS-C01 ふさわしい方式を選ぶのは一番重要なのです。
AWS Certified Specialty MLS-C01試験過去問 - AWS Certified Machine Learning - Specialty Goldmile-Infobizを選ぶなら、輝い未来を選ぶのに等しいです。 あなたが我々の資料を購入するとき、あなたのAmazonのMLS-C01 資格参考書試験に関するすべてのヘルプを購入しました。世界は変化している、我々はできるだけそのペースを維持する必要があります。
あなたはGoldmile-Infobizの学習教材を購入した後、私たちは一年間で無料更新サービスを提供することができます。あなたは最新のAmazonのMLS-C01試験過去問試験トレーニング資料を手に入れることが保証します。もしうちの学習教材を購入した後、試験に不合格になる場合は、私たちが全額返金することを保証いたします。
Amazon MLS-C01試験過去問 - これはあなたの能力を認めます。
Goldmile-Infobizは認定で優秀なIT資料のウエブサイトで、ここでAmazon MLS-C01試験過去問認定試験の先輩の経験と暦年の試験の材料を見つけることができるとともに部分の最新の試験の題目と詳しい回答を無料にダウンロードこともできますよ。弊社のIT技術専門家たち は質が高い問題集と答えを提供し、お客様が合格できるように努めています。
時間が経つとともに、我々はインタネット時代に生活します。この時代にはIT資格認証を取得するは重要になります。
MLS-C01 PDF DEMO:
QUESTION NO: 1
A Marketing Manager at a pet insurance company plans to launch a targeted marketing campaign on social media to acquire new customers Currently, the company has the following data in
Amazon Aurora
* Profiles for all past and existing customers
* Profiles for all past and existing insured pets
* Policy-level information
* Premiums received
* Claims paid
What steps should be taken to implement a machine learning model to identify potential new customers on social media?
A. Use a decision tree classifier engine on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media
B. Use a recommendation engine on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media
C. Use regression on customer profile data to understand key characteristics of consumer segments
Find similar profiles on social media.
D. Use clustering on customer profile data to understand key characteristics of consumer segments
Find similar profiles on social media.
Answer: B
QUESTION NO: 2
A Machine Learning Specialist is building a logistic regression model that will predict whether or not a person will order a pizza. The Specialist is trying to build the optimal model with an ideal classification threshold.
What model evaluation technique should the Specialist use to understand how different classification thresholds will impact the model's performance?
A. Receiver operating characteristic (ROC) curve
B. Misclassification rate
C. Root Mean Square Error (RM&)
D. L1 norm
Answer: A
QUESTION NO: 3
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: 4
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: 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