DataBytes-Organisation/Project-Echo
Nov 2024 – Dec 2024
2 Months active
Languages Used
Jupyter NotebookPython
Technical Skills
Audio AnalysisAudio ProcessingData AnalysisData ScienceData VisualizationFile Management
minhD03
PROFILE
Minhd03
Minh Dang developed core audio analysis and preprocessing features for the DataBytes-Organisation/Project-Echo repository over a two-month period. He created Jupyter Notebooks that introduced foundational audio concepts and demonstrated the impact of preprocessing steps such as bit-depth reduction and stereo-to-mono conversion on machine learning model performance. Minh refactored the project structure to improve discoverability and maintainability, and implemented FFT-based classification and feature extraction for automated course detection. Using Python, NumPy, and Librosa, he enhanced analysis workflows, improved file handling for audio datasets, and published clear documentation to support developer onboarding. His work emphasized practical, reproducible pipelines and robust project organization.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
7Total
Bugs
0
Commits
7
Features
5
Lines of code
7,789
Activity Months2
Your Network
47 people
Work History
December 2024
3 Commits • 2 Features
Dec 1, 2024December 2024 — DataBytes-Organisation/Project-Echo: Delivered the core Course Detection and Audio Analysis capability, with FFT-based classification and feature extraction, plus performance metrics capture to support optimization. Notebook refinements improved the analysis workflow (adjusted audio paths, frequency ranges, and run counts) and file counting now correctly handles subdirectories and .mp3 inputs with updated outputs. Published a new end-user reference document, Code Explaination for Engine Model, under Tutorials (no code changes) to clarify engine model usage. Overall, the focus was on feature delivery and documentation, advancing automated course detection and analysis reliability while providing clearer developer guidance.
3 Commits • 2 Features
Dec 1, 2024December 2024 — DataBytes-Organisation/Project-Echo: Delivered the core Course Detection and Audio Analysis capability, with FFT-based classification and feature extraction, plus performance metrics capture to support optimization. Notebook refinements improved the analysis workflow (adjusted audio paths, frequency ranges, and run counts) and file counting now correctly handles subdirectories and .mp3 inputs with updated outputs. Published a new end-user reference document, Code Explaination for Engine Model, under Tutorials (no code changes) to clarify engine model usage. Overall, the focus was on feature delivery and documentation, advancing automated course detection and analysis reliability while providing clearer developer guidance.
December 2024
November 2024
4 Commits • 3 Features
Nov 1, 20242024-11 monthly summary for DataBytes-Organisation/Project-Echo focused on delivering practical value through feature initiatives, repository improvements, and experimentation that informs audio preprocessing for ML workflows.
November 2024
4 Commits • 3 Features
Nov 1, 20242024-11 monthly summary for DataBytes-Organisation/Project-Echo focused on delivering practical value through feature initiatives, repository improvements, and experimentation that informs audio preprocessing for ML workflows.
Activity
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Quality Metrics
Correctness85.6%
Maintainability88.6%
Architecture85.8%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Audio AnalysisAudio ProcessingData AnalysisData ScienceData VisualizationFile ManagementJupyter NotebookJupyter NotebooksLibrosaMachine LearningMachine Learning (basic feature extraction)MatplotlibNumPyPandasProject Structure
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline