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AWS Certified Specialty MLS-C01 Goldmile-Infobizには専門的なエリート団体があります。
Goldmile-Infobiz のAmazonのMLS-C01 - AWS Certified Machine Learning - Specialty教育資料認証証明書はあなたが自分の知識と技能を高めることに助けになれることだけでなく、さまざまな条件であなたのキャリアを助けることもできます。 いろいろな受験生に通用します。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。
Goldmile-InfobizのAmazonのMLS-C01教育資料「AWS Certified Machine Learning - Specialty」トレーニング資料を利用したら、初めて試験を受けるあなたでも一回で試験に合格できることを保証します。Goldmile-InfobizのAmazonのMLS-C01教育資料トレーニング資料を利用しても合格しないのなら、我々は全額で返金することができます。あなたに他の同じ値段の製品を無料に送って差し上げます。
Amazon MLS-C01教育資料 - IT職員のキャリアと関連しますから。
我々社はAmazon MLS-C01教育資料問題集をリリースされる以来、たくさんの好評を博しました。試験に合格したお客様は「MLS-C01教育資料問題集のオンライン版を利用して、模擬試験を繰り返して受けました。無事試験に合格しました。Goldmile-Infobizから大変助かりました。」と感謝します。あなたの支持こそ我々は最も高品質のAmazon MLS-C01教育資料問題集を開発して努力します。
ですから、躊躇しないではやく試験を申し込みましょう。AmazonのMLS-C01教育資料認定試験は最近最も人気のある試験ですから、受験したいのですか。
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