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AWS Certified Specialty MLS-C01 できるだけ100％の通過率を保証使用にしています。
ブームになるIT技術業界でも、多くの人はこういう悩みがあるんですから、AmazonのMLS-C01 - AWS Certified Machine Learning - Specialty日本語版試験解答の能力を把握できるのは欠かさせないない技能であると考えられます。 ただ、社会に入るIT卒業生たちは自分能力の不足で、MLS-C01 模試エンジン試験向けの仕事を探すのを悩んでいますか？それでは、弊社のAmazonのMLS-C01 模試エンジン練習問題を選んで実用能力を速く高め、自分を充実させます。その結果、自信になる自己は面接のときに、面接官のいろいろな質問を気軽に回答できて、順調にMLS-C01 模試エンジン向けの会社に入ります。
我々社のAmazon MLS-C01日本語版試験解答問題集を購入するかどうかと疑問があると、弊社OmgzlookのMLS-C01日本語版試験解答問題集のサンプルをしてみるのもいいことです。試用した後、我々のMLS-C01日本語版試験解答問題集はあなたを試験に順調に合格させると信じられます。なぜと言うのは、我々社の専門家は改革に応じて問題の更新と改善を続けていくのは出発点から勝つからです。
また、Amazon MLS-C01日本語版試験解答問題集は的中率が高いです。
多分、MLS-C01日本語版試験解答テスト質問の数が伝統的な問題の数倍である。Amazon MLS-C01日本語版試験解答試験参考書は全ての知識を含めて、全面的です。そして、MLS-C01日本語版試験解答試験参考書の問題は本当の試験問題とだいたい同じことであるとわかります。MLS-C01日本語版試験解答試験参考書があれば,ほかの試験参考書を勉強する必要がないです。
簡単で順調にAmazon MLS-C01日本語版試験解答認定試験を通すのは問題になりますが、Omgzlookはこの問題を解決できるよ。弊社の問題集はIT技術者がこつこつ研究して、正確で最新なもので君のMLS-C01日本語版試験解答認定試験を簡単に通すことにいいトレーニングツールになりますよ。
MLS-C01 PDF DEMO:
QUESTION NO: 1
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: 2
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: 3
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: 4
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: 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