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AWS Certified Machine Learning – Associate Exam Prep and Study Guide: Comprehensive Coverage of all Exam Domains | 250+ Practice Questions with Answer Explanations | Exam Tips & Insights | Hand
The AWS Certified Machine Learning – Associate Exam Prep and Study Guide is your ultimate resource for building the skills and confidence needed to pass the AWS Certified Machine Learning – Associate exam. Designed to equip you with practical experience and exam-focused knowledge, this book systematically guides you through the end-to-end machine learning lifecycle on AWS.
A dedicated companion GitHub repository is included, providing hands-on lab guidance, including scripts, datasets, and supporting resources.
Comprehensive Machine Learning Coverage
From data ingestion and transformation to model training, deployment, and monitoring, this guide offers structured explanations, hands-on labs, and real-world examples. You'll explore feature engineering, dimensionality reduction, data wrangling, model evaluation, tuning, and advanced techniques like transfer learning and ensemble methods.
AWS ML Services & Tools
Master AWS machine learning services including Amazon SageMaker, Ground Truth, Data Wrangler, Feature Store, Clarify, Canvas, and Bedrock. Learn to leverage AWS AI services such as Comprehend, Translate, Rekognition, and Lex, while building scalable ML infrastructures using EMR, Glue, Kinesis, and more.
Practical, Hands-On Learning
Chapters combine foundational concepts with practical labs and best practices. Gain experience with SageMaker built-in algorithms, distributed training, securing ML workloads, setting up CI/CD pipelines, and monitoring model performance using SageMaker Model Monitor.
Exam-Focused Preparation
This guide
✅ 250+ Exam-style Practice Questions with Answer Analysis
✅ Comprehensive Coverage of all Exam Domains
✅ Exam Tips & Insights Hands-on Exercises
By combining structured theory, hands-on exercises, and exam-specific tips and insights, this book prepares you to pass the AWS Certified Machine Learning – Associate exam and confidently deploy ML solutions on AWS.
For additional tutorials and AWS guidance, visit the KnoDAX YouTube channel, featuring in-depth videos and walkthroughs to strengthen your practical skills.
Advance your career in AWS machine learning and cloud solutions with this comprehensive study guide today!
A dedicated companion GitHub repository is included, providing hands-on lab guidance, including scripts, datasets, and supporting resources.
Comprehensive Machine Learning Coverage
From data ingestion and transformation to model training, deployment, and monitoring, this guide offers structured explanations, hands-on labs, and real-world examples. You'll explore feature engineering, dimensionality reduction, data wrangling, model evaluation, tuning, and advanced techniques like transfer learning and ensemble methods.
AWS ML Services & Tools
Master AWS machine learning services including Amazon SageMaker, Ground Truth, Data Wrangler, Feature Store, Clarify, Canvas, and Bedrock. Learn to leverage AWS AI services such as Comprehend, Translate, Rekognition, and Lex, while building scalable ML infrastructures using EMR, Glue, Kinesis, and more.
Practical, Hands-On Learning
Chapters combine foundational concepts with practical labs and best practices. Gain experience with SageMaker built-in algorithms, distributed training, securing ML workloads, setting up CI/CD pipelines, and monitoring model performance using SageMaker Model Monitor.
Exam-Focused Preparation
This guide
✅ 250+ Exam-style Practice Questions with Answer Analysis
✅ Comprehensive Coverage of all Exam Domains
✅ Exam Tips & Insights Hands-on Exercises
By combining structured theory, hands-on exercises, and exam-specific tips and insights, this book prepares you to pass the AWS Certified Machine Learning – Associate exam and confidently deploy ML solutions on AWS.
For additional tutorials and AWS guidance, visit the KnoDAX YouTube channel, featuring in-depth videos and walkthroughs to strengthen your practical skills.
Advance your career in AWS machine learning and cloud solutions with this comprehensive study guide today!
590 pages, Kindle Edition
Published June 29, 2025
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