GET HIGH HIT RATE MLS-C01 FREE LEARNING CRAM AND PASS EXAM IN FIRST ATTEMPT

Get High Hit Rate MLS-C01 Free Learning Cram and Pass Exam in First Attempt

Get High Hit Rate MLS-C01 Free Learning Cram and Pass Exam in First Attempt

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The AWS Certified Machine Learning - Specialty exam is a rigorous and challenging test that requires a deep understanding of machine learning concepts and their applications on the AWS platform. Candidates are expected to have a strong foundation in mathematics, statistics, and computer science, as well as hands-on experience in building and deploying machine learning models. To succeed in MLS-C01 Exam, candidates should also be familiar with AWS services such as Amazon SageMaker, Amazon Rekognition, and Amazon Comprehend.

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Amazon AWS-Certified-Machine-Learning-Specialty (AWS Certified Machine Learning - Specialty) exam is a certification program designed for professionals who want to demonstrate their expertise in the field of machine learning. MLS-C01 Exam is intended to validate the knowledge and skills of candidates in building, training, and deploying machine learning models on the Amazon Web Services (AWS) platform.

The AWS-Certified-Machine-Learning-Specialty certification exam is a valuable credential for professionals who want to demonstrate their expertise in machine learning on the AWS platform. AWS Certified Machine Learning - Specialty certification validates an individual’s ability to design, implement, and deploy machine learning models on AWS, and passing the exam can lead to higher-paying job opportunities and access to the AWS Certified Community.

Amazon AWS Certified Machine Learning - Specialty Sample Questions (Q200-Q205):

NEW QUESTION # 200
A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided.

Based on this information which model would have the HIGHEST accuracy?

  • A. Logistic regression
  • B. Single perceptron with tanh activation function
  • C. Long short-term memory (LSTM) model with scaled exponential linear unit (SELL))
  • D. Support vector machine (SVM) with non-linear kernel

Answer: A


NEW QUESTION # 201
A health care company is planning to use neural networks to classify their X-ray images into normal and abnormal classes. The labeled data is divided into a training set of 1,000 images and a test set of 200 images.
The initial training of a neural network model with 50 hidden layers yielded 99% accuracy on the training set, but only 55% accuracy on the test set.
What changes should the Specialist consider to solve this issue? (Choose three.)

  • A. Include all the images from the test set in the training set
  • B. Enable early stopping
  • C. Enable dropout
  • D. Choose a smaller learning rate
  • E. Choose a higher number of layers
  • F. Choose a lower number of layers

Answer: A,C,E


NEW QUESTION # 202
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 regression on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media
  • B. Use clustering on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media
  • C. Use a recommendation engine on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media.
  • D. Use a decision tree classifier engine on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media.

Answer: C


NEW QUESTION # 203
A data scientist uses Amazon SageMaker Data Wrangler to define and perform transformations and feature engineering on historical data. The data scientist saves the transformations to SageMaker Feature Store.
The historical data is periodically uploaded to an Amazon S3 bucket. The data scientist needs to transform the new historic data and add it to the online feature store The data scientist needs to prepare the .....historic data for training and inference by using native integrations.
Which solution will meet these requirements with the LEAST development effort?

  • A. Use AWS Lambda to run a predefined SageMaker pipeline to perform the transformations on each new dataset that arrives in the S3 bucket.
  • B. Run an AWS Step Functions step and a predefined SageMaker pipeline to perform the transformations on each new dalaset that arrives in the S3 bucket
  • C. Use Apache Airflow to orchestrate a set of predefined transformations on each new dataset that arrives in the S3 bucket.
  • D. Configure Amazon EventBridge to run a predefined SageMaker pipeline to perform the transformations when a new data is detected in the S3 bucket.

Answer: D

Explanation:
Explanation
The best solution is to configure Amazon EventBridge to run a predefined SageMaker pipeline to perform the transformations when a new data is detected in the S3 bucket. This solution requires the least development effort because it leverages the native integration between EventBridge and SageMaker Pipelines, which allows you to trigger a pipeline execution based on an event rule. EventBridge can monitor the S3 bucket for new data uploads and invoke the pipeline that contains the same transformations and feature engineering steps that were defined in SageMaker Data Wrangler. The pipeline can then ingest the transformed data into the online feature store for training and inference.
The other solutions are less optimal because they require more development effort and additional services.
Using AWS Lambda or AWS Step Functions would require writing custom code to invoke the SageMaker pipeline and handle any errors or retries. Using Apache Airflow would require setting up and maintaining an Airflow server and DAGs, as well as integrating with the SageMaker API.
References:
Amazon EventBridge and Amazon SageMaker Pipelines integration
Create a pipeline using a JSON specification
Ingest data into a feature group


NEW QUESTION # 204
A large JSON dataset for a project has been uploaded to a private Amazon S3 bucket The Machine Learning Specialist wants to securely access and explore the data from an Amazon SageMaker notebook instance A new VPC was created and assigned to the Specialist How can the privacy and integrity of the data stored in Amazon S3 be maintained while granting access to the Specialist for analysis?

  • A. Launch the SageMaker notebook instance within the VPC and create an S3 VPC endpoint for the notebook to access the data Copy the JSON dataset from Amazon S3 into the ML storage volume on the SageMaker notebook instance and work against the local dataset
  • B. Launch the SageMaker notebook instance within the VPC and create an S3 VPC endpoint for the notebook to access the data Define a custom S3 bucket policy to only allow requests from your VPC to access the S3 bucket
  • C. Launch the SageMaker notebook instance within the VPC with SageMaker-provided internet access enabled. Generate an S3 pre-signed URL for access to data in the bucket
  • D. Launch the SageMaker notebook instance within the VPC with SageMaker-provided internet access enabled Use an S3 ACL to open read privileges to the everyone group

Answer: B

Explanation:
The best way to maintain the privacy and integrity of the data stored in Amazon S3 is to use a combination of VPC endpoints and S3 bucket policies. A VPC endpoint allows the SageMaker notebook instance to access the S3 bucket without going through the public internet. A bucket policy allows the S3 bucket owner to specify which VPCs or VPC endpoints can access the bucket. This way, the data is protected from unauthorized access and tampering. The other options are either insecure (A and D) or inefficient (B).
References: Using Amazon S3 VPC Endpoints, Using Bucket Policies and User Policies


NEW QUESTION # 205
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