What Will You Learn?
Describe ML concepts and life cycle phases
Describe metrics used for evaluating model candidates
Use SageMaker Data Wrangler to prepare tabular and time series data for training an ML model
Use SageMaker Autopilot to automatically build ML models and identify the best model from a list of model candidates based on your objective metric
Describe best practices for using SageMaker Data Wrangler and SageMaker Autopilot
About This Course
Provider: Skillbuilder
Format: Online
Duration: 4 hours to complete [Approx]
Target Audience: Intermediate
Learning Objectives: Learn Low-Code Machine Learning on AWS.
Course Prerequisites: We recommend that attendees of this course have:
• Experience with analysis, cleansing, and transforming tabular or time series data
• Basic understanding of statistical measures and regression
• AWS Technical Essentials
Assessment and Certification: NA
Instructor: NA
Key Topics: ML concepts and life cycle phases,automatically build ML models and identify the best model
Topic Covered:
-Introduction to Machine Learning
-Exploratory Data Analysis and Data Preparation
-Deep Dive on Amazon SageMaker Autopilot
-Operational Best Practices
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