ml_with_aws_sagemaker
Learn how to scale up ML/AI pipelines using AWS SageMaker (GPUs, Cloud computing)
https://github.com/carpentries-incubator/ml_with_aws_sagemaker
Science Score: 44.0%
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○Scientific vocabulary similarity
Low similarity (15.0%) to scientific vocabulary
Keywords
Repository
Learn how to scale up ML/AI pipelines using AWS SageMaker (GPUs, Cloud computing)
Basic Info
- Host: GitHub
- Owner: carpentries-incubator
- License: other
- Language: Jupyter Notebook
- Default Branch: main
- Homepage: https://carpentries-incubator.github.io/ML_with_AWS_SageMaker/
- Size: 11.5 MB
Statistics
- Stars: 1
- Watchers: 3
- Forks: 2
- Open Issues: 1
- Releases: 0
Topics
Metadata Files
README.md
The Carpentries Workbench Template Markdown Lesson
This lesson is a template lesson that uses The Carpentries Workbench.
Note about lesson life cycle stage
Although the config.yaml states the life cycle stage as pre-alpha, the template is stable and ready to use. The life cycle stage is preset to "pre-alpha" as this setting is appropriate for new lessons initialised using the template.
Create a new repository from this template
To use this template to start a new lesson repository,
make sure you're logged into Github.
Visit https://github.com/carpentries/workbench-template-md/generate
and follow the instructions.
Checking the 'Include all branches' option will save some time waiting for the first website build
when your new repository is initialised.
If you have any questions, contact @tobyhodges
Configure a new lesson
Follow the steps below to complete the initial configuration of a new lesson repository built from this template:
- Make sure GitHub Pages is activated:
navigate to Settings,
select Pages from the left sidebar,
and make sure that
gh-pagesis selected as the branch to build from. If nogh-pagesbranch is available, check Actions to see if the first website build workflows are still running. The branch should become available when those have completed. - Adjust the
config.yamlfile: this file contains global parameters for your lesson site. Individual fields within the file are documented with comments (beginning with#) At minimum, you should adjust all the fields marked 'FIXME':titlecreatedkeywordslife_cycle(the default, pre-alpha, is the appropriate for brand new lessons)contact
- Annotate the repository with site URL and topic tags:
navigate back to the repository landing page and
click on the gear wheel/cog icon (similar to ⚙️)
at the top-right of the About box.
Check the "Use your GitHub Pages website" option,
and add some keywords and other annotations to describe your lesson
in the Topics field.
At minimum, these should include:
lesson- the life cycle of the lesson (e.g.
pre-alpha) - the human language the lesson is written in (e.g.
deutsch)
- Adjust the
CITATION.cff,CODE_OF_CONDUCT.md,CONTRIBUTING.md, andLICENSE.mdfiles as appropriate for your project.-
CITATION.cff: this file contains information that people can use to cite your lesson, for example if they publish their own work based on it. You should update the CFF now to include information about your lesson, and remember to return to it periodicallt, keeping it updated as your author list grows and other details become available or need to change. The Citation File Format home page gives more information about the format, and thecffinitwebtool can be used to create new and update existing CFF files. -
CODE_OF_CONDUCT.md: if you are using this template for a project outside The Carpentries, you should adjust this file to describe who should be contacted with Code of Conduct reports, and how those reports will be handled. -
CONTRIBUTING.md: depending on the current state and maturity of your project, the contents of the template Contributing Guide may not be appropriate. You should adjust the file to help guide contributors on how best to get involved and make an impact on your lesson. -
LICENSE.md: in line with the terms of the CC-BY license, you should ensure that the copyright information provided in the license file is accurate for your project.
-
- Update this README with relevant information about your lesson and delete this section.
Owner
- Name: carpentries-incubator
- Login: carpentries-incubator
- Kind: organization
- Repositories: 107
- Profile: https://github.com/carpentries-incubator
Citation (CITATION.cff)
cff-version: 1.2.0
title: Intro to AWS SageMaker for Predictive ML/AI
message: >-
Please cite this lesson using the information in this file
when you refer to it in publications, and/or if you
re-use, adapt, or expand on the content in your own
training material.
type: dataset
authors:
- given-names: Christopher
family-names: Endemann
email: endemann@wisc.edu
affiliation: University of Wisconsin-Madison
orcid: 'https://orcid.org/0000-0002-7357-6129'
repository-code: >-
https://github.com/carpentries-incubator/ML_with_AWS_SageMaker
url: >-
https://carpentries-incubator.github.io/ML_with_AWS_SageMaker/index.html
abstract: >-
This workshop introduces foundational workflows in AWS
SageMaker, focusing on data setup, repository management,
model training, and hyperparameter tuning within AWS's
managed environment. Participants will learn to use
SageMaker notebooks to orchestrate data pipelines, launch
training and tuning jobs, and assess model performance.
The session will also cover strategies for scaling ML
workflows efficiently, including guidance on selecting
between CPU and GPU instances and leveraging parallelized
workflows across multiple instances. To support
cost-effective experimentation, the workshop provides best
practices for tracking and managing AWS expenses. While
AWS usage incurs costs, it can be an affordable solution
for research-oriented ML workflows. For example, training
approximately 100 small to medium-sized models (e.g.,
logistic regression, random forests, or lightweight deep
learning models with a few million parameters) on datasets
under 10GB can often be achieved for under $20. This
workshop is designed for researchers and practitioners
looking to implement scalable, cost-conscious ML workflows
using cloud-based infrastructure.
keywords:
- AWS
- Cloud Computing
- Machine Learning
- Artificial Intelligence
- SageMaker
- GPU
- Open-Source
- Carpentries Incubator
- Python
license: CC-BY-4.0
GitHub Events
Total
- Watch event: 1
- Issue comment event: 1
- Push event: 395
- Pull request event: 1
- Fork event: 2
- Create event: 1
Last Year
- Watch event: 1
- Issue comment event: 1
- Push event: 395
- Pull request event: 1
- Fork event: 2
- Create event: 1
Issues and Pull Requests
Last synced: 9 months ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
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- carpentries-bot (1)
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Dependencies
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- actions/checkout v4 composite
- carpentries/actions/check-valid-pr main composite
- carpentries/actions/comment-diff main composite
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- carpentries/actions/download-workflow-artifact main composite
- carpentries/actions/remove-branch main composite
- carpentries/actions/check-valid-pr main composite
- carpentries/actions/comment-diff main composite
- actions/checkout v4 composite
- actions/upload-artifact v4 composite
- carpentries/actions/check-valid-pr main composite
- carpentries/actions/setup-lesson-deps main composite
- carpentries/actions/setup-sandpaper main composite
- r-lib/actions/setup-pandoc v2 composite
- r-lib/actions/setup-r v2 composite
- actions/checkout v4 composite
- carpentries/actions/setup-lesson-deps main composite
- carpentries/actions/setup-sandpaper main composite
- r-lib/actions/setup-pandoc v2 composite
- r-lib/actions/setup-r v2 composite
- actions/checkout v4 composite
- carpentries/actions/check-valid-credentials main composite
- carpentries/actions/update-lockfile main composite
- carpentries/create-pull-request main composite
- r-lib/actions/setup-r v2 composite
- actions/checkout v4 composite
- carpentries/actions/check-valid-credentials main composite
- carpentries/actions/update-workflows main composite
- carpentries/create-pull-request main composite