amazon-sagemaker-examples carlosportella16 · COMPLETED
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
github.com/carlosportella16/amazon-sagemaker-examples · ★ 2 · Forks 0 · Size 634.2 MB
SUMMARY
Technologies 32
Scored 32
Observed 32
Practices 6
Evidence 33
Skips 0
COVERAGE
Analyzed 2860 files · 3118 commits · 0 API calls
TECHNOLOGIES & DEPTH
Java LANGUAGE Depth 70
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Dockerfile LANGUAGE Depth 70
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Shell LANGUAGE Depth 70
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C LANGUAGE Depth 70
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XML LANGUAGE Depth 70
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JavaScript LANGUAGE Depth 70
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JSON LANGUAGE Depth 70
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Markdown LANGUAGE Depth 70
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TOML LANGUAGE Depth 70
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YAML LANGUAGE Depth 70
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Python LANGUAGE Depth 70
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Maven BUILD_TOOL Depth 80
1 files · CONFIGURATION
pip BUILD_TOOL Depth 80
1 files · CONFIGURATION
AWS SDK CLOUD Depth 85
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FastAPI FRAMEWORK Depth 45
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Flask FRAMEWORK Depth 100
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Jackson LIBRARY Depth 66
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Jinja2 LIBRARY Depth 66
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Lombok LIBRARY Depth 58
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MongoDB DATABASE Depth 80
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NumPy LIBRARY Depth 100
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PostgreSQL DATABASE Depth 65
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Pydantic LIBRARY Depth 45
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RabbitMQ MESSAGE_BROKER Depth 88
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Redis CACHE Depth 88
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Requests LIBRARY Depth 85
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Spring Boot FRAMEWORK Depth 44
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Spring Framework FRAMEWORK Depth 74
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TypeScript LANGUAGE Depth 85
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Uvicorn LIBRARY Depth 45
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pandas LIBRARY Depth 85
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pytest TESTING Depth 64
5 files · TEST
PRACTICES
documentation · observedautomated_tests · observedcontinuous_integration · absentcontainerization · observedlinting · absentformatting · absent
ACTIVITY & OWNERSHIP
First commit 2017-10-25
Last commit 2024-06-24
Active months 81
Commits 3118