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所在平台: Udemy |
课程主页: https://www.udemy.com/course/pass-mla-c01-aws-certified-machine-learning-exam-in-3-days/
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课程名称：在3天内通过MLA-C01 AWS认证机器学习考试 课程概述： 本课程旨在帮助学员掌握AWS认证机器学习工程师助理的关键ML概念，并自信地通过考试。通过模拟真实考试模式的问题，涵盖所有重要主题，使学员充分准备。课程内容包含详细的解释和问题分析，以强化学员的理解和提升解决问题的能力。 第一部分：课程内容 - 各种实践测试题模拟真实考试结构，涵盖数据工程、探索性数据分析、建模和AWS上的ML模型部署等主题。 - 每道题目均提供详细的解释，帮助学员理解复杂的机器学习概念，从而提高解决问题的能力。 第二部分：示例题目 1. 关于客户流失预测模型的评估，分析混淆矩阵并判断模型的可行性，选择正确的答案，并理解为何选该答案（例如：对于假阳性和假阴性的成本分析）。 2. SageMaker训练工作的必需参数配置，理解IAM角色的重要性和输出路径的作用。 3. 为优化Amazon Athena的查询性能，选择最佳的存储格式（如Parquet文件的优势）。 课程亮点： - 测试你的知识，提高信心，模拟真实考试体验，发展考试策略； - 内容最新，确保覆盖AWS机器学习工程师助理考试的相关、高影响力概念。 本课程适合希望成为AWS认证机器学习工程师的学员，以及希望提升其机器学习技能的云专业人士。立即开始，踏出成为认证机器学习工程师的重要一步！
MLA-C01 AWS Certified Machine Learning Engineer Associate Exam Practice Test CourseFree 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: CExplanation: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: ACFExplanation: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 filesB. Parquet filesC. Compressed JSOND. RecordIOCorrect Answer: BExplanation: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?Our AWS Certified Machine Learning Engineer - Associate Practice Test Course is designed to help you master key ML concepts on AWS and confidently pass the exam. With realistic, exam-style questions covering all critical topics, this course ensures you're fully prepared to succeed!Why This Practice Test Course?Test Your Knowledge - Challenge yourself with comprehensive practice questions that mirror the real exam structure and cover topics such as data engineering, exploratory data analysis, modeling, and ML model deployment on AWS.Learn as You Go - Each question comes with detailed explanations to reinforce your understanding, clarify complex ML concepts, and improve your problem-solving skills.Boost Your Confidence - Simulate the actual exam experience, develop test-taking strategies, and walk into the exam fully prepared.Up-to-Date Content - All questions are aligned with the latest AWS Machine Learning Engineer - Associate exam objectives, ensuring you focus on relevant, high-impact concepts.Join thousands of aspiring machine learning engineers, data scientists, and cloud professionals who have sharpened their skills and achieved certification success. Get started today and take a big step toward becoming a certified AWS Machine Learning Engineer!
