Getting Started with Amazon SageMaker Studio
Developers working with machine learning will be able to put their knowledge to work with this practical guide to Amazon SageMaker Studio. The book takes a hands-on approach to implementing real-world machine learning use cases that will have you up and running quickly.
Offered by
Difficulty Level
Intermediate
Completion Time
10h52m
Language
English
About Book
Who Is This Book For?
This book is for data scientists and machine learning engineers who are looking to become well-versed with Amazon SageMaker Studio and gain hands-on machine learning experience to handle every step in the ML lifecycle, including building data as well as training and hosting models. Although basic knowledge of machine learning and data science is necessary, no previous knowledge of SageMaker Studio and cloud experience is required.
Getting Started with Amazon SageMaker Studio
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 10h52m total length
Machine Learning and Its Life Cycle in the Cloud
Introducing Amazon SageMaker Studio
Data Preparation with SageMaker Data Wrangler
Building a Feature Repository with SageMaker Feature Store
Building and Training ML Models with SageMaker Studio IDE
Detecting ML Bias and Explaining Models with SageMaker Clarify
Hosting ML Models in the Cloud: Best Practices
Jumpstarting ML with SageMaker JumpStart and Autopilot
Training ML Models at Scale in SageMaker Studio
Monitoring ML Models in Production with SageMaker Model Monitor
Operationalize ML Projects with SageMaker Projects, Pipelines and Model Registry
Related Resources
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