intel/AI-PC-Samples
Jul 2025 – Jul 2025
1 Month active
Languages Used
HTMLJavaScriptShell
Technical Skills
HTMLJavaScriptMachine LearningONNX Runtime WebTransformers.jsWebGPU
Rakshith
PROFILE
Rakshith
Contributed to the intel/AI-PC-Samples repository by developing and organizing comprehensive WebNN workshop content and sample applications. The work involved creating new directories to house WebNN applications and samples, updating project documentation to reflect these additions, and removing outdated checkpoint files to streamline the repository. Using JavaScript, HTML, and WebNN, the developer focused on improving onboarding for WebNN by clarifying the project structure and reducing clutter. No major bugs were addressed during this period, with efforts concentrated on feature development and repository maintenance. This foundational work supports future demonstrations and broader adoption of WebNN within the project’s ecosystem.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
8,549
Activity Months1
Your Network
2122 peopleSame Organization
@intel.com2109
Work History
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for intel/AI-PC-Samples: Delivered WebNN Workshop content and samples, introduced new directories for WebNN applications and samples, updated the README to reflect additions, and removed obsolete checkpoint files. No other major bugs documented this month. Overall, the work enhances WebNN onboarding, clarifies project structure, and reduces repository clutter, laying groundwork for broader WebNN demonstrations.
1 Commits • 1 Features
Jul 1, 2025July 2025 monthly summary for intel/AI-PC-Samples: Delivered WebNN Workshop content and samples, introduced new directories for WebNN applications and samples, updated the README to reflect additions, and removed obsolete checkpoint files. No other major bugs documented this month. Overall, the work enhances WebNN onboarding, clarifies project structure, and reduces repository clutter, laying groundwork for broader WebNN demonstrations.
July 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
HTMLJavaScriptShell
Technical Skills
HTMLJavaScriptMachine LearningONNX Runtime WebTransformers.jsWebGPUWebNN
Repositories Contributed To
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