sagemaker-distributed-training-workshop and sagemaker-end-to-end-workshop

Maintenance 6/25
Adoption 10/25
Maturity 16/25
Community 23/25
Maintenance 0/25
Adoption 8/25
Maturity 16/25
Community 20/25
Stars: 153
Forks: 67
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 61
Forks: 30
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT-0
No Package No Dependents
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About sagemaker-distributed-training-workshop

aws-samples/sagemaker-distributed-training-workshop

Hands-on workshop for distributed training and hosting on SageMaker

This workshop helps machine learning engineers and researchers optimize large neural networks for training on AWS. You'll learn how to take your existing model and data, apply distributed training techniques like data and model parallelism, and significantly reduce training time and resource costs. This is for professionals building and deploying AI models at scale.

deep-learning model-training performance-optimization cloud-ml large-scale-ai

About sagemaker-end-to-end-workshop

aws-samples/sagemaker-end-to-end-workshop

Hands-on end-to-end workshop to explore Amazon SageMaker.

This workshop helps businesses automate the identification of customers likely to churn. By using historical customer data, it trains a machine learning model to predict which current customers are at risk of leaving. The output is a prediction of customer churn, enabling proactive intervention. It is designed for data scientists and machine learning engineers looking to build and deploy customer churn prediction systems.

customer-retention churn-prediction data-science-workflow machine-learning-operations customer-analytics

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