Goldmile-Infobiz는 몇년간 최고급 덤프품질로 IT인증덤프제공사이트중에서 손꼽히는 자리에 오게 되었습니다. Amazon AWS-Certified-Machine-Learning-Specialty공부문제 덤프는 많은 덤프들중에서 구매하는 분이 많은 인기덤프입니다. Amazon AWS-Certified-Machine-Learning-Specialty공부문제시험준비중이신 분이시라면Amazon AWS-Certified-Machine-Learning-Specialty공부문제한번 믿고 시험에 도전해보세요. Goldmile-Infobiz의 덤프선택으로Amazon AWS-Certified-Machine-Learning-Specialty공부문제인증시험에 응시한다는 것 즉 성공과 멀지 않았습니다. 여러분의 성공을 빕니다. 이는 응시자가 확실하고도 빠르게Amazon AWS-Certified-Machine-Learning-Specialty공부문제덤프를 마스터하고Amazon AWS-Certified-Machine-Learning-Specialty공부문제시험을 패스할수 있도록 하는 또 하나의 보장입니다.
AWS Certified Machine Learning AWS-Certified-Machine-Learning-Specialty 통과율이 100%입니다.
Goldmile-Infobiz 의 학습가이드에는Amazon AWS-Certified-Machine-Learning-Specialty - AWS Certified Machine Learning - Specialty공부문제인증시험의 예상문제, 시험문제와 답입니다. 많은 사이트에서 판매하고 있는 시험자료보다 출중한Goldmile-Infobiz의 Amazon AWS-Certified-Machine-Learning-Specialty 최신덤프자료덤프는 실제시험의 거의 모든 문제를 적중하여 고득점으로 시험에서 한방에 패스하도록 해드립니다. Amazon AWS-Certified-Machine-Learning-Specialty 최신덤프자료시험은Goldmile-Infobiz제품으로 간편하게 도전해보시면 후회없을 것입니다.
여러분이 다른 사이트에서도Amazon인증AWS-Certified-Machine-Learning-Specialty공부문제시험 관련덤프자료를 보셨을 것입니다 하지만 우리Goldmile-Infobiz의 자료만의 최고의 전문가들이 만들어낸 제일 전면적이고 또 최신 업데이트일 것입니다.우리덤프의 문제와 답으로 여러분은 꼭 한번에Amazon인증AWS-Certified-Machine-Learning-Specialty공부문제시험을 패스하실 수 있습니다.
Goldmile-Infobiz에서 제공하는Amazon Amazon AWS-Certified-Machine-Learning-Specialty공부문제덤프로 시험 준비하세요.
최근 Amazon인증 AWS-Certified-Machine-Learning-Specialty공부문제시험이 IT업계에서 제일 높은 인지도를 가지고 있습니다.바라만 보지 마시고Amazon인증 AWS-Certified-Machine-Learning-Specialty공부문제시험에 도전해보세요. Goldmile-Infobiz 의 Amazon인증 AWS-Certified-Machine-Learning-Specialty공부문제덤프로 시험준비공부를 하시면 한방에 시험패스 가능합니다. Amazon인증 AWS-Certified-Machine-Learning-Specialty공부문제덤프로 자격증취득에 가까워지고 나아가서는 IT업계에서 인정을 받는 열쇠를 소유한것과 같다고 할수 있습니다.
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AWS-Certified-Machine-Learning-Specialty PDF DEMO:
QUESTION NO: 1
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: 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 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
QUESTION NO: 4
A Machine Learning Specialist kicks off a hyperparameter tuning job for a tree-based ensemble model using Amazon SageMaker with Area Under the ROC Curve (AUC) as the objective metric This workflow will eventually be deployed in a pipeline that retrains and tunes hyperparameters each night to model click-through on data that goes stale every 24 hours With the goal of decreasing the amount of time it takes to train these models, and ultimately to decrease costs, the Specialist wants to reconfigure the input hyperparameter range(s) Which visualization will accomplish this?
A. A scatter plot with points colored by target variable that uses (-Distributed Stochastic Neighbor
Embedding (I-SNE) to visualize the large number of input variables in an easier-to-read dimension.
B. A scatter plot showing (he performance of the objective metric over each training iteration
C. A histogram showing whether the most important input feature is Gaussian.
D. A scatter plot showing the correlation between maximum tree depth and the objective metric.
Answer: A
QUESTION NO: 5
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
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Updated: May 28, 2022