たぶん、あなたは苦しく準備してAmazonのMLS-C01資格準備試験に合格できないのを心配しています。おそらくあなたはお金がかかって買ったソフトが役に立たないのを心配しています。我々Goldmile-Infobizのあなたに開発するAmazonのMLS-C01資格準備ソフトはあなたの問題を解決することができます。 弊社が提供した問題集がほかのインターネットに比べて問題のカーバ範囲がもっと広くて対応性が強い長所があります。Goldmile-Infobizが持つべきなIT問題集を提供するサイトでございます。 我々Goldmile-Infobizが自分のソフトに自信を持つのは我々のAmazonのMLS-C01資格準備ソフトでAmazonのMLS-C01資格準備試験に参加する皆様は良い成績を取りましたから。
AWS Certified Specialty MLS-C01 商品の税金について、この問題を心配できません。
AWS Certified Specialty MLS-C01資格準備 - AWS Certified Machine Learning - Specialty Goldmile-Infobizのトレーニング資料は実践の検証に合格すたもので、多くの受験生に証明された１００パーセントの成功率を持っている資料です。 我々SiteName}を選択するとき、Amazon MLS-C01 日本語版参考書試験にうまく合格できるチャンスを捉えるといえます。Amazon MLS-C01 日本語版参考書ソフト版問題集のようなバーチャルは購入前に、どうすれば適用性を感じられますか。
ショートカットは一つしかないです。それはGoldmile-InfobizのAmazonのMLS-C01資格準備試験トレーニング資料を利用することです。これは全てのIT認証試験を受ける受験生のアドバイスです。
Amazon MLS-C01資格準備 - ふさわしい方式を選ぶのは一番重要なのです。
Goldmile-Infobizの経験豊富な専門家チームはAmazonのMLS-C01資格準備認定試験に向かって専門性の問題集を作って、とても受験生に合っています。Goldmile-Infobizの商品はIT業界中で高品質で低価格で君の試験のために専門に研究したものでございます。
現在あなたに提供するのは大切なAmazonのMLS-C01資格準備資料です。あなたの購入してから、我々はあなたにAmazonのMLS-C01資格準備資料の更新情況をつど提供します。
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