Fernando-JAL/Neurociencias-2025-2
Jan 2025 – May 2025
3 Months active
Languages Used
TextJupyter NotebookPythonJSON
Technical Skills
DocumentationConfusion MatrixData VisualizationDecision TreesJupyter NotebooksMachine Learning
CaroDaniells
PROFILE
Carodaniells
Over a three-month period, contributed to the Fernando-JAL/Neurociencias-2025-2 repository by developing four features focused on machine learning and data analysis for neuroimaging applications. Delivered Jupyter Notebooks demonstrating decision tree modeling, confusion matrix evaluation, and comparative analysis of CNN and Random Forest classifiers for brain tumor detection. Enhanced project documentation by defining learning objectives and created reproducible workflows for data visualization and reporting. Leveraged Python, scikit-learn, and TensorFlow to implement end-to-end solutions supporting data-driven decision-making and onboarding. The work emphasized clarity, reproducibility, and educational value, providing reusable artifacts for both technical demonstrations and collaborative research tasks.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
6Total
Bugs
0
Commits
6
Features
4
Lines of code
1,156
Activity Months3
Your Network
37 peopleSame Organization
@comunidad.unam.mx17
Work History
May 2025
3 Commits • 2 Features
May 1, 2025May 2025 performance summary for Fernando-JAL/Neurociencias-2025-2: Delivered two high-value features enhancing data exploration, reporting, and ML diagnosis capabilities. Implemented a new Jupyter Notebook (Tarea2MOD_Carolina.ipynb) for data visualization and reporting with embedded images, and built brain tumor classification models using CNN and Random Forest with training, evaluation, and a comparative analysis showing Random Forest as more accurate and consistent. No major bugs fixed this month; focus was on feature delivery and ML experimentation. The work strengthens data-driven decision support and reproducibility for neuroimaging tasks.
3 Commits • 2 Features
May 1, 2025May 2025 performance summary for Fernando-JAL/Neurociencias-2025-2: Delivered two high-value features enhancing data exploration, reporting, and ML diagnosis capabilities. Implemented a new Jupyter Notebook (Tarea2MOD_Carolina.ipynb) for data visualization and reporting with embedded images, and built brain tumor classification models using CNN and Random Forest with training, evaluation, and a comparative analysis showing Random Forest as more accurate and consistent. No major bugs fixed this month; focus was on feature delivery and ML experimentation. The work strengthens data-driven decision support and reproducibility for neuroimaging tasks.
May 2025
April 2025
2 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for Fernando-JAL/Neurociencias-2025-2. Key feature delivered: Machine Learning Notebook: Decision Trees on Iris with Pruned/Unpruned Trees and Evaluation. This work provides an end-to-end notebook demonstrating creation, training, pruning variants, and visualization of decision trees, plus generation of confusion matrices to evaluate model performance. No major bugs reported this period. Overall impact: delivers a reusable, educational ML notebook suite that supports reproducible experiments, demos for stakeholders, and faster onboarding for ML tasks in the Neurociencias project. Technologies demonstrated: Python, Jupyter notebooks, scikit-learn, data visualization, confusion matrix construction, and model evaluation. Commit references: a1441b6d58d564eecfdbf8bb81a7292a683fb04a; 9071a739c60cde3abbb23f1ea9540d2c8dc04fe5.
April 2025
2 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for Fernando-JAL/Neurociencias-2025-2. Key feature delivered: Machine Learning Notebook: Decision Trees on Iris with Pruned/Unpruned Trees and Evaluation. This work provides an end-to-end notebook demonstrating creation, training, pruning variants, and visualization of decision trees, plus generation of confusion matrices to evaluate model performance. No major bugs reported this period. Overall impact: delivers a reusable, educational ML notebook suite that supports reproducible experiments, demos for stakeholders, and faster onboarding for ML tasks in the Neurociencias project. Technologies demonstrated: Python, Jupyter notebooks, scikit-learn, data visualization, confusion matrix construction, and model evaluation. Commit references: a1441b6d58d564eecfdbf8bb81a7292a683fb04a; 9071a739c60cde3abbb23f1ea9540d2c8dc04fe5.
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary: Delivered foundational documentation in Fernando-JAL/Neurociencias-2025-2 by creating 'expectativascaro.txt' containing a single line expressing a learning goal related to machine learning, virtual reality, and rehabilitation. This clarifies objectives for ML/VR rehab initiatives and improves onboarding and cross-team collaboration. No major bugs reported this month. Commit: 1d42bedd62bb8a4b2b37435883c2a1b5e5435d80.
1 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary: Delivered foundational documentation in Fernando-JAL/Neurociencias-2025-2 by creating 'expectativascaro.txt' containing a single line expressing a learning goal related to machine learning, virtual reality, and rehabilitation. This clarifies objectives for ML/VR rehab initiatives and improves onboarding and cross-team collaboration. No major bugs reported this month. Commit: 1d42bedd62bb8a4b2b37435883c2a1b5e5435d80.
January 2025
Activity
Loading activity data...
Quality Metrics
Correctness76.6%
Maintainability76.6%
Architecture76.6%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONJupyter NotebookPythonText
Technical Skills
Confusion MatrixData AnalysisData VisualizationDecision TreesDeep LearningDocumentationImage ClassificationJupyter NotebookJupyter NotebooksKerasMachine LearningMatplotlibNumPyOpenCVPandas
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline