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AWS Certified Machine Learning - Specialty (MLS-C01) Cert Prep: 3 Modeling

Offered By: LinkedIn Learning

Tags

Machine Learning Courses Supervised Learning Courses Unsupervised Learning Courses Hyperparameter Optimization Courses Classification Courses Model Selection Courses Model Evaluation Courses

Course Description

Overview

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Learn about modeling, the process of choosing and training the right machine-learning model, to prepare for the AWS Certified Machine Learning – Specialty (MLS-C01) certification.

Syllabus

Introduction
  • Overview
1. Frame Business Problems as Machine Learning Problems
  • Determine when to use and when not to use ML
  • Know the difference between supervised and unsupervised learning
  • Select from among classification, regression, forecasting, clustering, recommendation, and more
2. Select the Appropriate Model(s) for a Given Machine Learning Problem
  • Select models
  • SageMaker Canvas demo
3. Train Machine Learning Models
  • Train validation test split, cross-validation
  • Optimization
  • Compute choice
4. Perform Hyperparameter Optimization
  • Neural network architecture
5. Evaluate Machine Learning Models
  • Avoid overfitting and underfitting
  • Select metrics
  • Compare models using metrics
Conclusion
  • Conclusion

Taught by

Noah Gift

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