AWS Certified Machine Learning: Model Training & Evaluation

Amazon Web Services 2021    |    Intermediate
  • 12 Videos | 35m 54s
  • Includes Assessment
  • Earns a Badge
Training a machine learning (ML) model is the first step of many when developing ML applications that enable businesses to discover new trends within broad and diverse data sets. Use this course to learn more about SageMaker's built-in algorithm and perform model training, evaluation, monitoring, tuning, and deployment using Amazon Elastic Compute Cloud (EC2) instances. Begin by examining factorization machines and the selection of EC2 instances. Next, you'll discover how to perform model training, evaluation, and deployment. You'll wrap up the course by exploring the steps involved in tuning and testing ML models. After you're done with this course, you'll have the skills and knowledge to successfully train and evaluate a model, further preparing you for the AWS Certified Machine Learning – Specialty certification exam.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    describe how factorization machines work and specify why they are powerful tools for recommender systems
    list and describe EC2 instances that can be used with SageMaker
    work with training recommender system on Amazon Reviews dataset using Python and SageMaker
    demonstrate how to reduce cost while training machine learning algorithms using Spot instances
    evaluate a trained machine learning algorithm
  • deploy a machine learning model using API endpoints
    monitor API usage in real-time
    work with feature engineering and machine learning experimentations using Python and SageMaker
    demonstrate how to run hyperparameter tuning jobs with SageMaker using Python and Amazon Reviews dataset
    conduct A/B testing for models trained on Amazon Reviews dataset using production variants
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    53s
    UP NEXT
  • Playable
    2. 
    Factorization Machines
    2m 54s
  • Locked
    3. 
    EC2 Instances
    3m 15s
  • Locked
    4. 
    Training with EC2 Instances
    3m 14s
  • Locked
    5. 
    Training with EC2 Spot Instances
    1m 24s
  • Locked
    6. 
    Evaluating Machine Learning Models
    1m 1s
  • Locked
    7. 
    Deploying Machine Learning Models
    6m 19s
  • Locked
    8. 
    Monitoring Machine Learning Models
    1m 55s
  • Locked
    9. 
    Working with Feature Engineering
    3m 38s
  • Locked
    10. 
    Performing Hyperparameter Tuning
    3m 19s
  • Locked
    11. 
    Using Production Variants
    2m 28s
  • Locked
    12. 
    Course Summary
    34s

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