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MLS-C01 認定テキスト - MLS-C01 資格復習テキスト & AWS Certified Machine Learning Specialty - Royalholidayclubbed
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AWS Certified Specialty MLS-C01 心はもはや空しくなく、生活を美しくなります。
MLS-C01 - AWS Certified Machine Learning - Specialty認定テキスト問題集は、あなたに異なるシステムバージョンを提供します。 また、MLS-C01 合格問題問題集に疑問があると、メールで問い合わせてください。現在IT技術会社に通勤しているあなたは、AmazonのMLS-C01 合格問題試験認定を取得しましたか？MLS-C01 合格問題試験認定は給料の増加とジョブのプロモーションに役立ちます。
MLS-C01認定テキスト試験に合格するには、たくさん時間と精力が必要です。しかし、Amazon MLS-C01認定テキスト試験参考書を選ばれば、試験に合格するだけでなく、時間を節約できます。だから、Amazon MLS-C01認定テキスト試験参考書を早く購入しましょう！
Amazon MLS-C01認定テキスト - 弊社の商品が好きなのは弊社のたのしいです。
あなたは弊社の商品を買ったら一年間に無料でアップサービスが提供された認定試験に合格するまで利用しても喜んでいます。もしテストの内容が変われば、すぐにお客様に伝えます。弊社はあなた１００％合格率を保証いたします。
Royalholidayclubbed を選択して１００％の合格率を確保することができて、もし試験に失敗したら、Royalholidayclubbedが全額で返金いたします。
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
RoyalholidayclubbedはAmazonのMicrosoft PL-900認定試験「AWS Certified Machine Learning - Specialty」に向けてもっともよい問題集を研究しています。 あなたはインターネットでAmazonのMicrosoft PL-600J認証試験の練習問題と解答の試用版を無料でダウンロードしてください。 CompTIA CAS-004 - Royalholidayclubbedの問題集は最大のお得だね！ NREMT EMT - Royalholidayclubbedはまた一年間に無料なサービスを更新いたします。 Huawei H20-684_V1.0 - Royalholidayclubbedというサイトをクッリクしたらあなたの願いを果たせます。
Updated: May 28, 2022
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