我々の商品にあなたを助けさせましょう。チャンスはいつも準備がある人のために存在しています。IT業界で就職する前に、あなたはAmazonのAWS-Certified-Machine-Learning-Specialty最新資料試験に合格したら、あなたに満足させる仕事を探す準備をよくしました。 AmazonのAWS-Certified-Machine-Learning-Specialty最新資料認証試験を選んだ人々が一層多くなります。AWS-Certified-Machine-Learning-Specialty最新資料試験がユニバーサルになりましたから、あなたはGoldmile-Infobiz のAmazonのAWS-Certified-Machine-Learning-Specialty最新資料試験問題と解答￥を利用したらきっと試験に合格するができます。 弊社のAWS-Certified-Machine-Learning-Specialty最新資料問題集は大勢の専門家たちの努力で開発される成果です。
AWS Certified Machine Learning AWS-Certified-Machine-Learning-Specialty 人生には様々な選択があります。
AWS-Certified-Machine-Learning-Specialty - AWS Certified Machine Learning - Specialty最新資料認定試験の問題集は大勢の人の注目を集め、とても人気がある商品です。 このような保証があれば、Goldmile-InfobizのAWS-Certified-Machine-Learning-Specialty 問題数問題集を購入しようか購入するまいかと躊躇する必要は全くないです。この問題集をミスすればあなたの大きな損失ですよ。
だから、私たちは信頼されるに値します。AWS-Certified-Machine-Learning-Specialty最新資料試験に合格するには、関連する教材を探す必要があります。しかし、Amazonのウエブサイトを見ると、すぐいいAWS-Certified-Machine-Learning-Specialty最新資料教材を手に入れることができます。
Amazon AWS-Certified-Machine-Learning-Specialty最新資料 - Goldmile-Infobizには専門的なエリート団体があります。
AmazonのAWS-Certified-Machine-Learning-Specialty最新資料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Goldmile-Infobizは君の試験の問題を準備してしまいました。君の初めての合格を目標にします。
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AWS-Certified-Machine-Learning-Specialty 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