もちろんです。Goldmile-InfobizのAmazonのMLS-C01受験準備試験トレーニング資料を持っていますから、どんなに難しい試験でも成功することができます。逆境は人をテストすることができます。 Goldmile-Infobizを選んだら、成功の手を握ることがきるようになります。全てのIT職員はAmazonのMLS-C01受験準備試験をよく知っています。 現在の仕事に満足していますか。
AWS Certified Specialty MLS-C01 あなた準備しましたか。
AWS Certified Specialty MLS-C01受験準備 - AWS Certified Machine Learning - Specialty 信じられなら利用してみてください。 あなたがする必要があるのは、問題集に出るすべての問題を真剣に勉強することです。この方法だけで、試験を受けるときに簡単に扱うことができます。
ここで私は明確にしたいのはGoldmile-InfobizのMLS-C01受験準備問題集の核心価値です。Goldmile-Infobizの問題集は100％の合格率を持っています。Goldmile-InfobizのMLS-C01受験準備問題集は多くのIT専門家の数年の経験の結晶で、高い価値を持っています。
Amazon MLS-C01受験準備認定試験は現在で本当に人気がある試験ですね。
我々Goldmile-Infobizは最高のアフターサービスを提供いたします。AmazonのMLS-C01受験準備試験ソフトを買ったあなたは一年間の無料更新サービスを得られて、AmazonのMLS-C01受験準備の最新の問題集を了解して、試験の合格に自信を持つことができます。あなたはAmazonのMLS-C01受験準備試験に失敗したら、弊社は原因に関わらずあなたの経済の損失を減少するためにもらった費用を全額で返しています。
どうやって安くて正確性の高いAmazonのMLS-C01受験準備問題集を買いますか。Goldmile-Infobizは最も安い値段で正確性の高いAmazonのMLS-C01受験準備問題集を提供します。
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 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: 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