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What Exam Is Necessary for AWS Machine Learning – Specialty?

The only test necessary to take the AWS Machine Learning – Specialty certification has the code MLS-C This is a specialty exam and it is delivered in English, Japanese, Korean, and Simplified Chinese. Candidates can use two types of delivery methods:

• In testing centers;
• Online using a proctored exam platform.

The registration fee for the AWS MLS-C01 exam is $300. In case candidates want to enroll in doing a practice exam, they should pay another $40. MLS-C01 test includes two types of questions. Candidates will have to answer both multiple-choice and multiple-answer items. Besides, the passing score range goes from 100 to 1,000 points. A candidate will be successful only when he/she gets a minimum score of 750 points. After successfully completing this MLS-C01 exam, you will be awarded the AWS Certified Machine Learning Specialty certification. If you add this certificate to your resume and social network, your chances to get better salary offers are higher. Also, this certification is valid for three years. But once its validity expires, you will need to check the vendor's official site for recertification. >> AWS-Certified-Machine-Learning-Specialty Practice Braindumps <<

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Amazon AWS Certified Machine Learning - Specialty Sample Questions (Q91-Q96):

NEW QUESTION # 91
A Data Scientist is developing a machine learning model to predict future patient outcomes based on information collected about each patient and their treatment plans. The model should output a continuous value as its prediction. The data available includes labeled outcomes for a set of
4,000 patients. The study was conducted on a group of individuals over the age of 65 who have a particular disease that is known to worsen with age.
Initial models have performed poorly. While reviewing the underlying data, the Data Scientist notices that, out of 4,000 patient observations, there are 450 where the patient age has been input as 0. The other features for these observations appear normal compared to the rest of the sample population How should the Data Scientist correct this issue?

• A. Replace the age field value for records with a value of 0 with the mean or median value from the dataset
• B. Drop the age feature from the dataset and train the model using the rest of the features.
• C. Drop all records from the dataset where age has been set to 0.
• D. Use k-means clustering to handle missing features

Answer: A Explanation:
For k-means you should do additional derivation of feasible number of clusters which is not a trivial task.
NEW QUESTION # 92
A machine learning (ML) specialist wants to secure calls to the Amazon SageMaker Service API. The specialist has configured Amazon VPC with a VPC interface endpoint for the Amazon SageMaker Service API and is attempting to secure traffic from specific sets of instances and IAM users. The VPC is configured with a single public subnet.
Which combination of steps should the ML specialist take to secure the traffic? (Choose two.)

• A. Add a SageMaker Runtime VPC endpoint interface to the VPC.
• B. Modify the security group on the endpoint network interface to restrict access to the instances.
• C. Modify the ACL on the endpoint network interface to restrict access to the instances.
• D. Modify the users' IAM policy to allow access to Amazon SageMaker Service API calls only.
• E. Add a VPC endpoint policy to allow access to the IAM users.

Answer: B,E
NEW QUESTION # 93
A company is setting up an Amazon SageMaker environment. The corporate data security policy does not allow communication over the internet.
How can the company enable the Amazon SageMaker service without enabling direct internet access to Amazon SageMaker notebook instances?

• A. Create a NAT gateway within the corporate VPC.
• B. Create VPC peering with Amazon VPC hosting Amazon SageMaker.
• C. Route Amazon SageMaker traffic through an on-premises network.
• D. Create Amazon SageMaker VPC interface endpoints within the corporate VPC.

Answer: A
NEW QUESTION # 94
A Machine Learning Specialist trained a regression model, but the first iteration needs optimizing. The Specialist needs to understand whether the model is more frequently overestimating or underestimating the target.
What option can the Specialist use to determine whether it is overestimating or underestimating the target value?

• A. Residual plots
• B. Root Mean Square Error (RMSE)
• C. Area under the curve
• D. Confusion matrix

Answer: A
NEW QUESTION # 95
A Machine Learning Specialist is packaging a custom ResNet model into a Docker container so the company can leverage Amazon SageMaker for training. The Specialist is using Amazon EC2 P3 instances to train the model and needs to properly configure the Docker container to leverage the NVIDIA GPUs.
What does the Specialist need to do?

• A. Set the GPU flag in the Amazon SageMaker CreateTrainingJob request body.
• B. Build the Docker container to be NVIDIA-Docker compatible.
• C. Organize the Docker container's file structure to execute on GPU instances.
• D. Bundle the NVIDIA drivers with the Docker image.

Answer: B Explanation:
https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-dg.pdf
If you plan to use GPU devices, make sure that your containers are nvidia-docker compatible.
Only the CUDA toolkit should be included on containers. Don't bundle NVIDIA drivers with the image.
For more information about nvidia-docker, see NVIDIA/nvidia-docker.
NEW QUESTION # 96
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