Chameleon-company/MOP-Code
May 2025 – May 2025
1 Month active
Languages Used
Jupyter NotebookPythonSQL
Technical Skills
Code CleanupData PreprocessingDeep LearningFile ManagementKerasMNE
Alen Antony
PROFILE
Alen Antony
During May 2025, S223276239 developed an end-to-end CNN-LSTM sleep stage classification notebook for the Chameleon-company/MOP-Code repository, targeting the Sleep-EDF family of datasets. Their work encompassed data loading, preprocessing, model construction, training, and evaluation, all within a Jupyter Notebook environment using Python, Keras, and TensorFlow. By updating and clarifying the main model notebook and removing outdated code, S223276239 streamlined the repository, reducing confusion and maintenance overhead. The approach emphasized reproducibility and rapid experimentation, supporting clearer modeling workflows. Their contributions demonstrated depth in deep learning, data preprocessing, and code cleanup, resulting in a more maintainable and business-focused codebase.
Overall Statistics
Feature vs Bugs
50%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
1
Lines of code
2,014
Activity Months1
Your Network
186 people
Work History
May 2025
3 Commits • 1 Features
May 1, 2025May 2025 monthly summary for Chameleon-company/MOP-Code: Delivered an end-to-end CNN-LSTM sleep stage classification notebook across Sleep-EDF datasets, enabling rapid experimentation, reproducibility, and clearer modeling workflows. Repository cleanup removed an outdated notebook to reduce confusion and maintenance burden. The work emphasizes data loading, preprocessing, model building, training, and evaluation, with an emphasis on business value through faster prototyping and clearer documentation.
3 Commits • 1 Features
May 1, 2025May 2025 monthly summary for Chameleon-company/MOP-Code: Delivered an end-to-end CNN-LSTM sleep stage classification notebook across Sleep-EDF datasets, enabling rapid experimentation, reproducibility, and clearer modeling workflows. Repository cleanup removed an outdated notebook to reduce confusion and maintenance burden. The work emphasizes data loading, preprocessing, model building, training, and evaluation, with an emphasis on business value through faster prototyping and clearer documentation.
May 2025
Activity
Loading activity data...
Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPythonSQL
Technical Skills
Code CleanupData PreprocessingDeep LearningFile ManagementKerasMNEMNE-PythonMachine LearningModel EvaluationModel TrainingNumPyPandasPythonScikit-learnTensorFlow
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline