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
Fernando contributed to the Fernando-JAL/Neurociencias-2025-2 repository by developing machine learning notebooks focused on regression metrics visualization and a decision tree classifier with overfitting analysis, using Python and Jupyter Notebook. He implemented a practical exam for brain tumor detection, building an end-to-end image classification pipeline with data splitting, augmentation, and a convolutional neural network using Keras and TensorFlow. Fernando also maintained repository hygiene by documenting learning goals and updating the Python environment for reproducibility. His work demonstrated a solid grasp of data analysis, model evaluation, and environment management, providing practical tools for both personal learning and project advancement.
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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