Exam MLS-C01 Papers | MLS-C01 Latest Exam Forum

Each Amazon certification exam candidate know this certification related to the major shift in their lives. Amazon Certification MLS-C01 Exam training materials DumpsValid provided with ultra-low price and high quality immersive questions and answersdedication to the majority of candidates. Our products have a cost-effective, and provide one year free update. Our certification training materials are all readily available. Our website is a leading supplier of the answers to dump. We have the latest and most accurate certification exam training materials what you need.

What is the duration of the AWS Certified Machine Learning - Specialty

Number of Questions: 54
Passing Score: 720
Language : English, Japanese, Korean, and Simplified Chinese
Format: Multiple choices, multiple answers
Length of Examination: 130 minutes

Achieving the Amazon MLS-C01 Certification is an excellent way for professionals to demonstrate their expertise in machine learning and to advance their careers. It is also a valuable credential for organizations that are looking to hire skilled professionals in the field of machine learning. By becoming certified in Amazon MLS-C01, candidates can show their dedication to staying current with the latest trends and technologies in the rapidly evolving field of machine learning.

>> Exam MLS-C01 Papers <<

Amazon MLS-C01 Exam | Exam MLS-C01 Papers - Bringing Candidates Good MLS-C01 Latest Exam Forum

Free demo for MLS-C01 exam bootcamp is available, and you can have a try before buying, so that you can have a deeper understanding of what you are going to buy. In addition, MLS-C01 exam materials are high-quality and accuracy, and therefore you can use the exam materials with ease. In order to build up your confidence for MLS-C01 Exam Dumps, we are pass guarantee and money back guarantee, and if you fail to pass the exam, we will give you full refund. We have online and offline service for MLS-C01 exam brainudmps, and if you have any questions, you can consult us, and we will give you reply as quickly as we can.

To be eligible for the AWS Certified Machine Learning - Specialty certification exam, candidates must have a minimum of one year of experience in developing and maintaining machine learning models on the AWS platform. They must also have a strong understanding of AWS services, such as Amazon SageMaker, Amazon EC2, Amazon S3, and AWS Lambda.

Amazon AWS Certified Machine Learning - Specialty Sample Questions (Q323-Q328):

NEW QUESTION # 323
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 near-realtime data insights; Amazon Kinesis Data Firehose for clickstream analytics; AWS Glue to generate personalized product recommendations
B. 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
C. 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
D. 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

Answer: B

NEW QUESTION # 324
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?

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

Answer: A

Explanation:
Explanation
The ML specialist should run the Model Monitor baseline job again on the new training set and configure Model Monitor to use the new baseline. This is because the baseline job computes the statistics and constraints for the data quality and model quality metrics, which are used to detect violations. If the training set changes, the baseline job should be updated accordingly to reflect the new distribution of the data and the model performance. Otherwise, the old baseline may not be representative of the current production traffic and may cause false alarms or miss violations. References:
Monitor data and model quality - Amazon SageMaker
Detecting and analyzing incorrect model predictions with Amazon SageMaker Model Monitor and Debugger | AWS Machine Learning Blog

NEW QUESTION # 325
A company wants to use automatic speech recognition (ASR) to transcribe messages that are less than 60 seconds long from a voicemail-style application. The company requires the correct identification of 200 unique product names, some of which have unique spellings or pronunciations.
The company has 4,000 words of Amazon SageMaker Ground Truth voicemail transcripts it can use to customize the chosen ASR model. The company needs to ensure that everyone can update their customizations multiple times each hour.
Which approach will maximize transcription accuracy during the development phase?

A. Create a custom vocabulary file containing each product name with phonetic pronunciations, and use it with Amazon Transcribe to perform the ASR customization. Analyze the transcripts and manually update the custom vocabulary file to include updated or additional entries for those names that are not being correctly identified.
B. Use a voice-driven Amazon Lex bot to perform the ASR customization. Create customer slots within the bot that specifically identify each of the required product names. Use the Amazon Lex synonym mechanism to provide additional variations of each product name as mis-transcriptions are identified in development.
C. Use Amazon Transcribe to perform the ASR customization. Analyze the word confidence scores in the transcript, and automatically create or update a custom vocabulary file with any word that has a confidence score below an acceptable threshold value. Use this updated custom vocabulary file in all future transcription tasks.
D. Use the audio transcripts to create a training dataset and build an Amazon Transcribe custom language model. Analyze the transcripts and update the training dataset with a manually corrected version of transcripts where product names are not being transcribed correctly. Create an updated custom language model.

Answer: A

Explanation:
The best approach to maximize transcription accuracy during the development phase is to create a custom vocabulary file containing each product name with phonetic pronunciations, and use it with Amazon Transcribe to perform the ASR customization. A custom vocabulary is a list of words and phrases that are likely to appear in your audio input, along with optional information about how to pronounce them. By using a custom vocabulary, you can improve the transcription accuracy of domain-specific terms, such as product names, that may not be recognized by the general vocabulary of Amazon Transcribe. You can also analyze the transcripts and manually update the custom vocabulary file to include updated or additional entries for those names that are not being correctly identified.
The other options are not as effective as option C for the following reasons:
Option A is not suitable because Amazon Lex is a service for building conversational interfaces, not for transcribing voicemail messages. Amazon Lex also has a limit of 100 slots per bot, which is not enough to accommodate the 200 unique product names required by the company.
Option B is not optimal because it relies on the word confidence scores in the transcript, which may not be accurate enough to identify all the mis-transcribed product names. Moreover, automatically creating or updating a custom vocabulary file may introduce errors or inconsistencies in the pronunciation or display of the words.
Option D is not feasible because it requires a large amount of training data to build a custom language model.
The company only has 4,000 words of Amazon SageMaker Ground Truth voicemail transcripts, which is not enough to train a robust and reliable custom language model. Additionally, creating and updating a custom language model is a time-consuming and resource-intensive process, which may not be suitable for the development phase where frequent changes are expected.
Amazon Transcribe - Custom Vocabulary
Amazon Transcribe - Custom Language Models
[Amazon Lex - Limits]

NEW QUESTION # 326
A Machine Learning Specialist is given a structured dataset on the shopping habits of a company's customer base. The dataset contains thousands of columns of data and hundreds of numerical columns for each customer. The Specialist wants to identify whether there are natural groupings for these columns across all customers and visualize the results as quickly as possible.
What approach should the Specialist take to accomplish these tasks?

A. Embed the numerical features using the t-distributed stochastic neighbor embedding (t-SNE) algorithm and create a scatter plot.
B. Embed the numerical features using the t-distributed stochastic neighbor embedding (t-SNE) algorithm and create a line graph.
C. Run k-means using the Euclidean distance measure for different values of k and create box plots for each numerical column within each cluster.
D. Run k-means using the Euclidean distance measure for different values of k and create an elbow plot.

Answer: D

NEW QUESTION # 327
A Machine Learning Specialist is developing a custom video recommendation model for an application The dataset used to train this model is very large with millions of data points and is hosted in an Amazon S3 bucket The Specialist wants to avoid loading all of this data onto an Amazon SageMaker notebook instance because it would take hours to move and will exceed the attached 5 GB Amazon EBS volume on the notebook instance.
Which approach allows the Specialist to use all the data to train the model?

A. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to the instance. Train on a small amount of the data to verify the training code and hyperparameters. Go back to Amazon SageMaker and train using the full dataset
B. Load a smaller subset of the data into the SageMaker notebook and train locally. Confirm that the training code is executing and the model parameters seem reasonable. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to train the full dataset.
C. Use AWS Glue to train a model using a small subset of the data to confirm that the data will be compatible with Amazon SageMaker. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.
D. Load a smaller subset of the data into the SageMaker notebook and train locally. Confirm that the training code is executing and the model parameters seem reasonable. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode.

Answer: D

NEW QUESTION # 328
......

MLS-C01 Latest Exam Forum: https://www.dumpsvalid.com/MLS-C01-still-valid-exam.html