ML-TANGO/TANGO
Oct 2024 – Mar 2025
3 Months active
Languages Used
ExcelJavaScriptPythonVueSQL
Technical Skills
Backend DevelopmentConfiguration ManagementFrontend DevelopmentDatabase ManagementDjangoAPI Development
gmlee
PROFILE
Gmlee
Gyeongmin Lee contributed to the ML-TANGO/TANGO repository by developing and refining backend and frontend features that improved deployment flexibility, data integrity, and user experience. He implemented enhanced target preset management and hardware accelerator support using Python and Django, expanding device compatibility and reducing configuration errors. Lee also introduced base64-encoded image handling and ordered target display, aligning the data model with UI requirements for more predictable operations. Addressing stability, he fixed data parsing issues by handling infinity values in training metrics and improved project configuration workflows with YAML editing. His work demonstrated depth in full stack development and configuration management.
Overall Statistics
Feature vs Bugs
60%Features
Repository Contributions
6Total
Bugs
2
Commits
6
Features
3
Lines of code
666
Activity Months3
Your Network
12 peopleSame Organization
@teslasystem.co.kr1
Work History
March 2025
3 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for ML-TANGO/TANGO focusing on stability, configuration flexibility, and UI safeguards.
3 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for ML-TANGO/TANGO focusing on stability, configuration flexibility, and UI safeguards.
March 2025
November 2024
1 Commits • 1 Features
Nov 1, 2024In 2024-11, ML-TANGO/TANGO delivered a targeted UX and data-model improvement: base64-encoded image support for targets, a new order field on the Target model, and sorting by order in loading/reading views. This results in a more organized, scalable target presentation and lays groundwork for user-defined sorting and batch operations. The work was committed under 8d4c9e059bfac76037b473142eb6248374ddf5ab ("Change default target order and image"), enabling predictable display and better data integrity for operators and downstream analytics.
November 2024
1 Commits • 1 Features
Nov 1, 2024In 2024-11, ML-TANGO/TANGO delivered a targeted UX and data-model improvement: base64-encoded image support for targets, a new order field on the Target model, and sorting by order in loading/reading views. This results in a more organized, scalable target presentation and lays groundwork for user-defined sorting and batch operations. The work was committed under 8d4c9e059bfac76037b473142eb6248374ddf5ab ("Change default target order and image"), enabling predictable display and better data integrity for operators and downstream analytics.
October 2024
2 Commits • 1 Features
Oct 1, 2024In 2024-10, ML-TANGO/TANGO delivered a set of enhancements to target preset management and hardware accelerator support, improving deployment flexibility and out-of-the-box usability. Key changes include updating the default target preset to support new target types and engines, ensuring a default image when none is provided, refactoring deployment type handling for clarity, and expanding target compatibility by adding new hardware accelerators in SecondStepper with an updated target info file. This reduces configuration errors, broadens device support, and accelerates time-to-value for customers.
2 Commits • 1 Features
Oct 1, 2024In 2024-10, ML-TANGO/TANGO delivered a set of enhancements to target preset management and hardware accelerator support, improving deployment flexibility and out-of-the-box usability. Key changes include updating the default target preset to support new target types and engines, ensuring a default image when none is provided, refactoring deployment type handling for clarity, and expanding target compatibility by adding new hardware accelerators in SecondStepper with an updated target info file. This reduces configuration errors, broadens device support, and accelerates time-to-value for customers.
October 2024
Activity
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Quality Metrics
Correctness86.6%
Maintainability86.6%
Architecture83.4%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
ExcelJavaScriptPythonSQLVue
Technical Skills
API DevelopmentBackend DevelopmentConfiguration ManagementData HandlingDatabase ManagementDjangoFrontend DevelopmentFull Stack Development
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