MLS-C01 공부문제 - Amazon AWS Certified Machine Learning Specialty 시험응시료 - Goldmile-Infobiz

Amazon인증MLS-C01공부문제시험은 IT인증시험과목중 가장 인기있는 시험입니다. Goldmile-Infobiz에서는Amazon인증MLS-C01공부문제시험에 대비한 공부가이드를 발췌하여 IT인사들의 시험공부 고민을 덜어드립니다. Goldmile-Infobiz에서 발췌한 Amazon인증MLS-C01공부문제덤프는 실제시험의 모든 범위를 커버하고 있고 모든 시험유형이 포함되어 있어 시험준비 공부의 완벽한 선택입니다. Goldmile-Infobiz시험공부자료를 선택하시면 자격증취득의 소원이 이루어집니다. Amazon인증MLS-C01공부문제시험덤프는Goldmile-Infobiz가 최고의 선택입니다. 거의 100%의 정확도를 자랑하고 있습니다.

AWS Certified Specialty MLS-C01 Goldmile-Infobiz에서 덤프를 마련하여 자격증취득에 도전하여 인생을 바꿔보세요.

Amazon인증 MLS-C01 - AWS Certified Machine Learning - Specialty공부문제시험준비자료는 Goldmile-Infobiz에서 마련하시면 기적같은 효과를 안겨드립니다. Amazon인증 MLS-C01 예상문제시험을 어떻게 패스할가 고민그만하고Goldmile-Infobiz의Amazon 인증MLS-C01 예상문제시험대비 덤프를 데려가 주세요.가격이 착한데 비해 너무나 훌륭한 덤프품질과 높은 적중율, Goldmile-Infobiz가 아닌 다른곳에서 찾아볼수 없는 혜택입니다.

Amazon인증 MLS-C01공부문제시험이 어려워 자격증 취득을 망설이는 분들이 많습니다. Goldmile-Infobiz가 있으면 이런 걱정은 하지 않으셔도 됩니다. Goldmile-Infobiz의Amazon인증 MLS-C01공부문제덤프로 시험을 한방에 통과하여 승진이나 연봉인상에 도움되는 자격증을 취득합시다.

Amazon MLS-C01공부문제 - 또한 구매후 일년무료 업데이트버전을 바을수 있는 기회를 얻을수 있습니다.

Amazon MLS-C01공부문제 덤프는Amazon MLS-C01공부문제시험문제변경에 따라 주기적으로 업데이트를 진행하여 저희 덤프가 항상 가장 최신버전이도록 보장해드립니다. 고객님들에 대한 깊은 배려의 마음으로 고품질Amazon MLS-C01공부문제덤프를 제공해드리고 디테일한 서비스를 제공해드리는것이 저희의 목표입니다.

Goldmile-Infobiz는 전문적으로 it인증시험관련문제와 답을 만들어내는 제작팀이 있으며, Pass4Tes 이미지 또한 업계에서도 이름이 있답니다 만약Amazon인증MLS-C01공부문제시험을 통과하고 싶다면, Pass4Tes의 선택을 추천합니다.

MLS-C01 PDF DEMO:

QUESTION NO: 1
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: 2
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: 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