課程大綱： Amazon SageMaker：簡化機器學習應用程序開發培訓
Welcome to Machine Learning with Amazon SageMakerCourse Introduction
Welcome to Machine Learning with SageMaker on AWS
Course Welcome and Student Information
Meet the Instructors
Introduce YourselfWeek 1Introduction to Machine Learning with SageMaker on AWS
Introduction to Week 1
What we we use ML for?
Diving Right In
What is Amazon SageMakerWeeklyQuiz, Readings, Resources, Discussion
Week 1 Notes and Resources
Week 1 Quiz
Week 1 DiscussionWeek 2Amazon SageMaker Notebooks and SDKIntroduction to Week 2Amazon SageMaker Notebooks
Introduction to Jupyter Notebooks
Notebooks and Libraries: Cleaning and Preparing Data
Exercise 2.1 Walkthrough
Exercise 2.1: Create Your Notebook Instance (Optional)Weekly Quiz, Readings, Resources, Discussion
Week 2 Notes and Resources
Week 2 Quiz
Week 2 DiscussionWeek 3Amazon SageMaker Algorithms
Introduction to Week 3ML and Amazon SageMaker Terminology
SageMaker/ML Terminology and Algorithms
Hyperparameter TuningAmazon SageMaker Algorithms
k-means Algorithm Walkthrough
Introduction to Exercise 3.1
Exercise 3.1: Using the k-means Algorithm (Optional)
XGBoost Algorithm Walkthrough (Part 1)
XGBoost Algorithm Walkthrough (Part 2)
XGBoost Algorithm Walkthrough (Part 3)
Introduction to Exercise 3.2
Exercise 3.2: Using the XGBoost Algorithm (Optional)Weekly Quiz, Readings, Resources, Discussion
Week 3 Notes and Resources
Week 3 Quiz
Week 3 DiscussionWeek 4Application Integration
Introduction to Week 4Integrating Amazon SageMaker with your Applications
Serverless Recap
Exercise 4.1 Walkthrough
Exercise 4.1: Python Movie Recommender (Optional)
Bring Your Own Models
Bringing Your Own Models: MXNet and TensorFlowWeekly Quiz, Readings, Resources, Discussion
Week 4 Notes and Resources
Week 4 Quiz
Class Wrap Up
Course Survey
Week 4 DiscussionEnd of Course Assessment (Verified Certificate Track Only)
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