sagemaker-explaining-credit-decisions
Amazon SageMaker Solution for explaining credit decisions.
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Download Latest Version (.zip)- glue.yaml
- sagemaker.yaml
- datasets.py
- lambda_function.py
- requirements.in
- solution-assistant.yaml
- template.yaml
- citation.txt
- german.data
- complete.png
- stage_1.png
- stage_2.png
- stage_3.png
- stage_4.png
- stage_5.png
- cleaning_up_youtube.png
- example_report.html
- explanations.png
- getting_started_youtube.png
- introduction_youtube.png
- launch_button.svg
- etl_job.py
- global_page.py
- local_page.py
- __init__.py
- app.py
- session_state.py
- shared.py
- Dockerfile
- requirements.in
- entry_point.py
- explaining.py
- training.py
- Dockerfile
- requirements.in
- 0_introduction.ipynb
- 1_datasets.ipynb
- 2_training.ipynb
- 3_endpoint.ipynb
- 4_batch_transform.ipynb
- 5_dashboard.ipynb
- 6_conclusion.ipynb
- __init__.py
- datasets.py
- glue.py
- schemas.py
- jumbotron.png
- styles.css
- template.html
- __init__.py
- reports.py
- __init__.py
- containers.py
- predictors.py
- __init__.py
- config.py
- utils.py
- visuals.py
- test_datasets.py
- test_schemas.py
- test_estimator_fns.py
- test_entry_point.py
- requirements.in
- setup.py
- env_setup.py
- setup.sh
- global_page.py
- local_page.py
- __init__.py
- app.py
- session_state.py
- shared.py
- Dockerfile
- requirements.in
- entry_point.py
- explaining.py
- get_sm_account.py
- training.py
- buildspec.yaml
- Dockerfile
- requirements.in
- 0_introduction.ipynb
- 1_datasets.ipynb
- 2_training.ipynb
- 3_endpoint.ipynb
- 4_batch_transform.ipynb
- 5_dashboard.ipynb
- 6_conclusion.ipynb
- __init__.py
- datasets.py
- glue.py
- schemas.py
- jumbotron.png
- styles.css
- template.html
- __init__.py
- reports.py
- __init__.py
- containers.py
- logs.py
- predictors.py
- __init__.py
- config.py
- utils.py
- visuals.py
- test_datasets.py
- test_schemas.py
- test_estimator_fns.py
- test_entry_point.py
- requirements.in
- setup.py
- env_setup.py
- setup.sh
- global_page.py
- local_page.py
- __init__.py
- app.py
- session_state.py
- shared.py
- Dockerfile
- requirements.in
- entry_point.py
- explaining.py
- get_sm_account.py
- training.py
- buildspec.yaml
- Dockerfile
- requirements.in
- 0_introduction.ipynb
- 1_datasets.ipynb
- 2_training.ipynb
- 3_endpoint copy.py
- 3_endpoint.ipynb
- 4_batch_transform.ipynb
- 5_conclusion.ipynb
- __init__.py
- datasets.py
- glue.py
- schemas.py
- jumbotron.png
- styles.css
- template.html
- __init__.py
- reports.py
- __init__.py
- containers.py
- logs.py
- predictors.py
- __init__.py
- config.py
- utils.py
- visuals.py
- test_datasets.py
- test_schemas.py
- test_estimator_fns.py
- test_entry_point.py
- requirements.in
- setup.py
- env_setup.py
- setup.sh
- .gitignore
- CODE_OF_CONDUCT.md
- CONTRIBUTING.md
- LICENSE
- NOTICE
- README.md
# Installation Guide
1. Get the code
git clone https://github.com/awslabs/sagemaker-explaining-credit-decisions
Downloads the entire project code from GitHub to your computer.
cd sagemaker-explaining-credit-decisions
Moves into the project folder you just downloaded.
2. Docker
Easy RecommendedPrerequisites
- Git Needed to download the project code from GitHub.
- Docker Desktop Needed to build and run containers. Install it and keep it running in the background.
* `Dockerfile`: Describes custom Docker image hosted on Amazon ECR.
Type this command into your terminal and run it.
* `requirements.txt`: Describes Python package requirements of the Docker image.
Runs the Python script (or module).
* `containers.py`: Manages the Docker workflow of building and pushing images to Amazon ECR.
Type this command into your terminal and run it.
Run docker compose ps to check the containers are Up. If the README mentions a port, open http://localhost:PORT in your browser.
Pulled directly from this repo's README.
3. Python
EasyPrerequisites
β οΈ This is a large repository, so this method may point to an internal sub-package rather than the actual core product. Check the full README as well.
pip install .
Installs the package published on PyPI directly β no need to clone the source.
jupyter notebook
Launches Jupyter in your browser so you can open and run the notebook (.ipynb) files.
If it runs without errors and prints output in the terminal, it worked.
// repository documentation
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