IBM/materials
Dec 2024 – Dec 2024
1 Month active
Languages Used
MarkdownPython
Technical Skills
data processingdependency managementdocumentationmachine learningmodel description
Eduardo Soares
PROFILE
Eduardo Soares
Contributed to the IBM/materials repository by delivering documentation and dependency scaffolding for the SMI-SSED model, which supports quantum property prediction workflows. Focused on improving onboarding and reproducibility, the work consolidated model description and dependency management into a single feature package. Using Python and Markdown, the developer detailed the SMI-SSED model’s capabilities and applications, while updating the requirements file to enable machine learning and data processing functionality. All changes were tracked through two commits to ensure traceability. This effort enhanced maintainability and aligned the repository with the project’s data science direction, providing a foundation for future quantum property prediction tasks.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
6
Activity Months1
Your Network
999 peopleSame Organization
@ibm.com988
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Abhina SreeMember
Abhishek KumarMember
Abhishek Kr SrivastavMember
Abraham Lara GranadosMember
Adapa ChathuryaMember
Work History
December 2024
2 Commits • 1 Features
Dec 1, 2024December 2024: Delivered documentation and dependency scaffolding for the SMI-SSED model in IBM/materials, enabling quantum property prediction workflows with ready-to-run ML/data processing. This work improves onboarding, reproducibility, and alignment with the project’s data science direction. All changes are tracked via two commits for traceability.
2 Commits • 1 Features
Dec 1, 2024December 2024: Delivered documentation and dependency scaffolding for the SMI-SSED model in IBM/materials, enabling quantum property prediction workflows with ready-to-run ML/data processing. This work improves onboarding, reproducibility, and alignment with the project’s data science direction. All changes are tracked via two commits for traceability.
December 2024
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage80.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
data processingdependency managementdocumentationmachine learningmodel description
Repositories Contributed To
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