Fernando-JAL/Neurociencias-2025-2
May 2025 – May 2025
1 Month active
Languages Used
Jupyter NotebookMarkdownPython
Technical Skills
Data AnalysisData PreprocessingData VisualizationDecision TreesDeep LearningExploratory Data Analysis (EDA)
Clau-CV
PROFILE
Clau-cv
Developed a suite of educational machine learning notebooks in the Fernando-JAL/Neurociencias-2025-2 repository, focusing on supervised learning, regression metrics, and medical image analysis. The work emphasized end-to-end workflows, including data loading, preprocessing, model training, and evaluation using Python, Jupyter Notebooks, and libraries such as Scikit-learn and TensorFlow. Projects included a Decision Tree Classifier on the Iris dataset, detailed regression metric documentation, and an initial brain tumor image analysis pipeline comparing CNN and Random Forest models. Consistent documentation and visualization practices were applied to enhance reproducibility, onboarding, and future extensibility, laying a foundation for broader adoption and further development.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
6Total
Bugs
0
Commits
6
Features
3
Lines of code
4,467
Activity Months1
Your Network
20 peopleWork History
May 2025
6 Commits • 3 Features
May 1, 2025May 2025 performance summary for Fernando-JAL/Neurociencias-2025-2: Delivered a compact suite of educational ML notebooks spanning supervised learning concepts, regression metrics, and medical image analysis. Focused on end-to-end pipelines, visualization, and reproducibility to accelerate learning, validation, and stakeholder understanding. No major bug fixes were recorded this month; the work lays the groundwork for broader adoption, future enhancements, and potential deployment-ready modules.
6 Commits • 3 Features
May 1, 2025May 2025 performance summary for Fernando-JAL/Neurociencias-2025-2: Delivered a compact suite of educational ML notebooks spanning supervised learning concepts, regression metrics, and medical image analysis. Focused on end-to-end pipelines, visualization, and reproducibility to accelerate learning, validation, and stakeholder understanding. No major bug fixes were recorded this month; the work lays the groundwork for broader adoption, future enhancements, and potential deployment-ready modules.
May 2025
Activity
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Quality Metrics
Correctness85.0%
Maintainability86.6%
Architecture83.4%
Performance83.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookMarkdownPython
Technical Skills
Data AnalysisData PreprocessingData VisualizationDecision TreesDeep LearningExploratory Data Analysis (EDA)Image ClassificationImage ProcessingJupyter NotebookJupyter NotebooksKerasMachine LearningMatplotlibModel EvaluationNumPy
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