aws-ml-enablement-workshop and aws-ml-jp

These are complementary resources where the enablement workshop provides organizational strategy and planning frameworks, while the Notebook collection supplies hands-on technical implementation guidance for building and deploying ML models on SageMaker.

aws-ml-jp
49
Emerging
Maintenance 20/25
Adoption 10/25
Maturity 16/25
Community 17/25
Maintenance 2/25
Adoption 10/25
Maturity 16/25
Community 21/25
Stars: 554
Forks: 60
Downloads:
Commits (30d): 21
Language: Jupyter Notebook
License: MIT-0
Stars: 168
Forks: 42
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT-0
No Package No Dependents
Stale 6m No Package No Dependents

About aws-ml-enablement-workshop

aws-samples/aws-ml-enablement-workshop

組織横断的にチームを組成し、機械学習による成長サイクルを実現する計画を立てるワークショップ

This workshop helps cross-functional teams, including business and development roles, plan and launch new products or features powered by AI/ML and generative AI. It takes your initial product ideas and guides you through an Amazon-style development process to create press releases, build functional mock-ups, and define a clear launch plan within 3-6 months. Product managers, business strategists, and development leads will use this to accelerate their AI product initiatives.

AI Product Strategy Generative AI Adoption Cross-functional Team Collaboration Product Launch Planning Customer-centric Development

About aws-ml-jp

aws-samples/aws-ml-jp

SageMakerで機械学習モデルを構築、学習、デプロイする方法が学べるNotebookと教材集

This collection of tutorials helps you build, train, and deploy machine learning models on AWS. It provides practical examples and guided lessons, showing you how to turn raw data into predictive models and integrate them into real-world applications. Data scientists, machine learning engineers, and application developers who want to leverage AWS for their ML projects will find this useful.

machine-learning-engineering predictive-analytics model-deployment data-science-workflow cloud-ml

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