Pass MLA-C01 AWS Certified Machine Learning Exam in 3 Days
MLA-C01AWS Certified Machine Learning Engineer Associate | Real Questions | Detail Explanations | Covers All Exam Topics

Pass MLA-C01 AWS Certified Machine Learning Exam in 3 Days udemy course free download
MLA-C01AWS Certified Machine Learning Engineer Associate | Real Questions | Detail Explanations | Covers All Exam Topics
MLA-C01 AWS Certified Machine Learning Engineer Associate Exam Practice Test Course
Free Sample Question 1 out of 3:
The customer analytics team at TelCo Solutions is developing a churn prediction model to proactively offer incentives, given that the cost of losing a customer is significantly higher than providing an incentive. The model produces the following confusion matrix after evaluating on a test dataset of 100 customers: Based on the model evaluation results, why is this a viable model for production?
A. The model is 86% accurate and the cost incurred by the company as a result of false negatives is less than the false positives.
B. The precision of the model is 86%, which is less than the accuracy of the model.
C. The model is 86% accurate and the cost incurred by the company as a result of false positives is less than the false negatives.
D. The precision of the model is 86%, which is greater than the accuracy of the model.
Correct Answer: C
Explanation:
The question states that the cost of churn is far greater than the cost of the incentive. Therefore, the model is viable if the cost of false positives (FP) is less than the cost of false negatives (FN).
* Accuracy: The accuracy of the model is (True Positives + True Negatives) / Total predictions = (10 + 76) / 100 = 86%.
* False Positives (FP): The model predicts the customer will churn, but they don't. The company offers an incentive unnecessarily. In this case FP = 10.
* False Negatives (FN): The model predicts the customer will not churn, but they do. The company does not offer an incentive, and the customer churns. In this case FN = 4.
Since the problem states "the cost of churn is far greater than the cost of the incentive," incurring 10 FPs is more acceptable than incurring 4 FNs. Option C reflects this understanding.
Free Sample Question 2 out of 3:
The Machine Learning team at Innovate Solutions is configuring SageMaker training jobs with built-in algorithms and needs to know the essential parameters for submission. Which common parameters MUST be specified? (Choose three.)
A. The training channel identifying the location of training data on an Amazon S3 bucket.
B. The validation channel identifying the location of validation data on an Amazon S3 bucket.
C. The IAM role that Amazon SageMaker can assume to perform tasks on behalf of the users.
D. Hyperparameters in a JSON array as documented for the algorithm used.
E. The Amazon EC2 instance class specifying whether training will be run using CPU or GPU.
F. The output path specifying where on an Amazon S3 bucket the trained model will persist.
Correct Answer: ACF
Explanation:
The common parameters that MUST be specified are: the training channel identifying the location of training data, the IAM role that SageMaker can assume, and the output path for the trained model.
Free Sample Question 3 out of 3:
The Data Insights team at "ScaleMetrics" needs to improve the query performance of their Amazon Athena analytics, which currently struggles with the 1 TB of metrics data generated every minute. What storage format in Amazon S3 will best improve query performance?
A. CSV files
B. Parquet files
C. Compressed JSON
D. RecordIO
Correct Answer: B
Explanation:
Parquet is a columnar storage format optimized for analytical queries in services like Amazon Athena. It allows Athena to read only the necessary columns, significantly reducing the amount of data scanned and improving query performance compared to row-based formats like CSV or JSON.
Are You Ready to Ace the AWS Certified Machine Learning Engineer - Associate Certification?
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