Free MLS-C01 Exam Braindumps (page: 39)

Page 39 of 84

A manufacturing company asks its machine learning specialist to develop a model that classifies defective parts into one of eight defect types. The company has provided roughly 100,000 images per defect type for training. During the initial training of the image classification model, the specialist notices that the validation accuracy is 80%, while the training accuracy is 90%. It is known that human-level performance for this type of image classification is around 90%.

What should the specialist consider to fix this issue?

  1. A longer training time
  2. Making the network larger
  3. Using a different optimizer
  4. Using some form of regularization

Answer(s): D


Reference:

https://acloud.guru/forums/aws-certified-machine-learning-specialty/discussion/-MGdBUKmQ02zC3uOq4VL/AWS%20Exam%20Machine%20Learning



A machine learning specialist needs to analyze comments on a news website with users across the globe. The specialist must find the most discussed topics in the comments that are in either English or Spanish.

What steps could be used to accomplish this task? (Choose two.)

  1. Use an Amazon SageMaker BlazingText algorithm to find the topics independently from language. Proceed with the analysis.
  2. Use an Amazon SageMaker seq2seq algorithm to translate from Spanish to English, if necessary. Use a SageMaker Latent Dirichlet Allocation (LDA) algorithm to find the topics.
  3. Use Amazon Translate to translate from Spanish to English, if necessary. Use Amazon Comprehend topic modeling to find the topics.
  4. Use Amazon Translate to translate from Spanish to English, if necessary. Use Amazon Lex to extract topics form the content.
  5. Use Amazon Translate to translate from Spanish to English, if necessary. Use Amazon SageMaker Neural Topic Model (NTM) to find the topics.

Answer(s): B


Reference:

https://docs.aws.amazon.com/sagemaker/latest/dg/lda.html



A machine learning (ML) specialist is administering a production Amazon SageMaker endpoint with model monitoring configured. Amazon SageMaker Model Monitor detects violations on the SageMaker endpoint, so the ML specialist retrains the model with the latest dataset. This dataset is statistically representative of the current production traffic. The ML specialist notices that even after deploying the new SageMaker model and running the first monitoring job, the SageMaker endpoint still has violations.

What should the ML specialist do to resolve the violations?

  1. Manually trigger the monitoring job to re-evaluate the SageMaker endpoint traffic sample.
  2. Run the Model Monitor baseline job again on the new training set. Configure Model Monitor to use the new baseline.
  3. Delete the endpoint and recreate it with the original configuration.
  4. Retrain the model again by using a combination of the original training set and the new training set.

Answer(s): B



A company supplies wholesale clothing to thousands of retail stores. A data scientist must create a model that predicts the daily sales volume for each item for each store. The data scientist discovers that more than half of the stores have been in business for less than 6 months. Sales data is highly consistent from week to week.

Daily data from the database has been aggregated weekly, and weeks with no sales are omitted from the current dataset. Five years (100 MB) of sales data is available in Amazon S3.
Which factors will adversely impact the performance of the forecast model to be developed, and which actions should the data scientist take to mitigate them? (Choose two.)

  1. Detecting seasonality for the majority of stores will be an issue. Request categorical data to relate new stores with similar stores that have more historical data.
  2. The sales data does not have enough variance. Request external sales data from other industries to improve the model's ability to generalize.
  3. Sales data is aggregated by week. Request daily sales data from the source database to enable building a daily model.
  4. The sales data is missing zero entries for item sales. Request that item sales data from the source database include zero entries to enable building the model.
  5. Only 100 MB of sales data is available in Amazon S3. Request 10 years of sales data, which would provide 200 MB of training data for the model.

Answer(s): A,C



Page 39 of 84



Post your Comments and Discuss Amazon MLS-C01 exam with other Community members:

Richard commented on October 24, 2023
i am thrilled to say that i passed my amazon web services mls-c01 exam, thanks to study materials. they were comprehensive and well-structured, making my preparation efficient.
Anonymous
upvote

Richard commented on October 24, 2023
I am thrilled to say that I passed my Amazon Web Services MLS-C01 exam, thanks to study materials. They were comprehensive and well-structured, making my preparation efficient.
Anonymous
upvote

Ken commented on October 13, 2021
I would like to share my good news with you about successfully passing my exam. This study package is very relevant and helpful.
AUSTRALIA
upvote

Alex commented on April 19, 2021
A very great in amount of questions are from real exam. Almost same wording. :)
SOUTH KOREA
upvote

MD ABU S CHOWDHURY commented on January 18, 2020
Working on the test..
UNITED STATES
upvote