ChandraLingam/AmazonSageMakerCourse

In this AWS Machine Learning Specialty Course, You will gain first-hand experience on how to train, optimize, deploy, and integrate ML in AWS cloud. Learn how to use AWS Built-in SageMaker algorithms and AI, How to Bring Your Own Algorithm, Zero Downtime Model Deployment Options, How to Integrate and Invoke ML from your Application, Automated Hyperparameter Tuning

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Established

This course teaches you how to build, refine, and deploy machine learning models on Amazon's cloud platform, AWS SageMaker. You'll learn to take raw data and transform it into working AI solutions ready for integration into your applications. This is designed for IT professionals, data scientists, and machine learning engineers who need to manage AI workflows in a cloud environment.

238 stars. No commits in the last 6 months.

Use this if you are an IT professional or data scientist looking to master the deployment and management of machine learning models on AWS SageMaker.

Not ideal if you are a business user looking for a no-code AI solution or if you prefer to build machine learning models without using cloud infrastructure.

cloud-machine-learning ML-operations data-science AWS-cloud model-deployment
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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Stars

238

Forks

408

Language

Jupyter Notebook

License

Last pushed

Mar 22, 2025

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