Fernando-JAL/Neurociencias-2025-2
Jan 2025 – May 2025
2 Months active
Languages Used
Jupyter NotebookPython
Technical Skills
CNNClassificationData AnalysisData AugmentationData VisualizationDecision Trees
Natanael501
PROFILE
Natanael501
Over a two-month period, contributed to the Fernando-JAL/Neurociencias-2025-2 repository by developing three features focused on machine learning and knowledge management. Delivered Jupyter notebooks for regression metrics visualization and a decision tree classifier with overfitting analysis, leveraging Python, scikit-learn, and data visualization libraries such as Matplotlib and Seaborn. Implemented a practical exam for brain tumor detection using convolutional neural networks, covering data augmentation, model training, and evaluation. Enhanced repository hygiene by documenting learning goals and updating the Python environment for reproducibility. The work demonstrated a methodical approach to building practical ML tools and maintaining a clean, well-documented codebase.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
5Total
Bugs
0
Commits
5
Features
3
Lines of code
1,108
Activity Months2
Your Network
37 peopleSame Organization
@comunidad.unam.mx17
Work History
May 2025
4 Commits • 2 Features
May 1, 2025May 2025 Summary for Fernando-JAL/Neurociencias-2025-2: Key deliverables include two ML notebooks for regression metrics visualization (MSE, MAE, RMSE, R²) and a 3-depth decision tree classifier with a confusion matrix and overfitting analysis, plus an environment update from Python 3.10.4 to 3.12.4 (commits: 87c89fe57979a4b5e327df670632ffe7075b8a8d; 9d20eb47af09f7bfa9b2ebe3209d2a422940ba47; f5feb5c5b8a39a53533cfd7f0da6ff3706fddacd). In addition, introduced a Brain Tumor Detection CNN Practical Exam covering data splitting, image augmentation, CNN model creation, training, and evaluation (commit: 09af2d0d73515ab9db6f3de46206a8cca7caaba1). Major bugs fixed: none reported this month. Overall impact: enhances learning tooling with practical ML evaluation capabilities, ensures reproducibility, and aligns notebooks with current Python libraries. Technologies/skills demonstrated: Python, Jupyter notebooks, regression metrics and visualization, decision trees, CNNs, data augmentation, model training/evaluation, environment management.
4 Commits • 2 Features
May 1, 2025May 2025 Summary for Fernando-JAL/Neurociencias-2025-2: Key deliverables include two ML notebooks for regression metrics visualization (MSE, MAE, RMSE, R²) and a 3-depth decision tree classifier with a confusion matrix and overfitting analysis, plus an environment update from Python 3.10.4 to 3.12.4 (commits: 87c89fe57979a4b5e327df670632ffe7075b8a8d; 9d20eb47af09f7bfa9b2ebe3209d2a422940ba47; f5feb5c5b8a39a53533cfd7f0da6ff3706fddacd). In addition, introduced a Brain Tumor Detection CNN Practical Exam covering data splitting, image augmentation, CNN model creation, training, and evaluation (commit: 09af2d0d73515ab9db6f3de46206a8cca7caaba1). Major bugs fixed: none reported this month. Overall impact: enhances learning tooling with practical ML evaluation capabilities, ensures reproducibility, and aligns notebooks with current Python libraries. Technologies/skills demonstrated: Python, Jupyter notebooks, regression metrics and visualization, decision trees, CNNs, data augmentation, model training/evaluation, environment management.
May 2025
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for Fernando-JAL/Neurociencias-2025-2: Key feature delivered: Added Learning Goals Documentation (Espectativas_Natanael) to capture personal learning goals for consolidating knowledge from the previous semester and exploring AI. Repository hygiene improvement: removed empty Ola.txt to reduce clutter. Commit reference: 8d1b5dadb46bd041e4522700b2ec13257a63e228 with message 'Espectativas'. Major bugs fixed: none reported for this repository this month. Overall impact: aligns personal development with project context, improves knowledge management, and keeps the codebase clean for future work. Technologies/skills demonstrated: Git version control with descriptive commits, documentation best practices, and basic file operations; evidence of proactive self-directed learning focused on AI.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for Fernando-JAL/Neurociencias-2025-2: Key feature delivered: Added Learning Goals Documentation (Espectativas_Natanael) to capture personal learning goals for consolidating knowledge from the previous semester and exploring AI. Repository hygiene improvement: removed empty Ola.txt to reduce clutter. Commit reference: 8d1b5dadb46bd041e4522700b2ec13257a63e228 with message 'Espectativas'. Major bugs fixed: none reported for this repository this month. Overall impact: aligns personal development with project context, improves knowledge management, and keeps the codebase clean for future work. Technologies/skills demonstrated: Git version control with descriptive commits, documentation best practices, and basic file operations; evidence of proactive self-directed learning focused on AI.
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Quality Metrics
Correctness88.0%
Maintainability88.0%
Architecture88.0%
Performance84.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
CNNClassificationData AnalysisData AugmentationData VisualizationDecision TreesDeep LearningEnvironment ManagementImage ClassificationKerasMachine LearningMatplotlibNumPyPandasRegression
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