AmazonSageMakerCourse and AWS-Machine-Learning

AmazonSageMakerCourse
51
Established
AWS-Machine-Learning
35
Emerging
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 0/25
Adoption 5/25
Maturity 16/25
Community 14/25
Stars: 238
Forks: 408
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License:
Stars: 12
Forks: 3
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About AmazonSageMakerCourse

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

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.

cloud-machine-learning ML-operations data-science AWS-cloud model-deployment

About AWS-Machine-Learning

vvead/AWS-Machine-Learning

AWS Maching Learning Foundations Scholarship

This project offers a practical introduction to machine learning concepts using AWS services and devices. It allows users to experiment with different AI domains like computer vision, reinforcement learning, and generative AI. You can input camera feeds for object detection, simulate race car behavior for autonomous driving, or provide musical melodies to generate new compositions.

Machine Learning Foundations Computer Vision Reinforcement Learning Generative AI Cloud Computing

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