Learn Amazon SageMaker
This book will teach you how to move quickly from business questions to machine learning models in production. Using real-world examples implemented with Python and Jupyter notebooks, you’ll learn about many the features and APIs of Amazon SageMaker on a wide spectrum of use cases: tabular data, computer vision, and natural language processing.
Offered by
Difficulty Level
Intermediate
Completion Time
16h20m
Language
English
About Book
Who Is This Book For?
This book is for software engineers, machine learning developers, data scientists, and AWS users who are new to using Amazon SageMaker and want to build high-quality machine learning models without worrying about infrastructure. Knowledge of AWS basics is required to grasp the concepts covered in this book more effectively. Some understanding of machine learning concepts and the Python programming language will also be beneficial.
Learn Amazon SageMaker
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 16h20m total length
Getting Started with Amazon SageMaker
Handling Data Preparation Techniques
AutoML with Amazon SageMaker AutoPilot
Training Machine Learning Models
Training Computer Vision Models
Training Natural Language Processing Models
Extending Machine Learning Services Using Built-In Frameworks
Using Your Algorithms and Code
Scaling Your Training Jobs
Advanced Training Techniques
Deploying Machine Learning Models
Automating Machine Learning Workflows
Optimizing Prediction Cost and Performance
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