Fernando-JAL/Neurociencias-2025-2
Jan 2025 – May 2025
3 Months active
Languages Used
MarkdownPython
Technical Skills
CNNClassificationData AnalysisData PreprocessingData ScienceData Visualization
zairaval
PROFILE
Zairaval
Zaira Avila developed end-to-end machine learning solutions in the Fernando-JAL/Neurociencias-2025-2 repository, focusing on brain tumor image classification using convolutional neural networks. She implemented and evaluated a CNN model in Python with TensorFlow and Keras, comparing its performance to traditional machine learning approaches. Zaira also created Jupyter notebooks for educational purposes, covering data preprocessing, exploratory data analysis, and model evaluation to support neuroscience coursework and final projects. Her work included repository hygiene improvements, such as removing extraneous files and standardizing metadata, which enhanced maintainability and reproducibility. The contributions demonstrated depth in both technical implementation and project organization.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
9Total
Bugs
1
Commits
9
Features
4
Lines of code
3,131
Activity Months3
Your Network
37 people
Work History
May 2025
6 Commits • 3 Features
May 1, 2025May 2025 (2025-05) summary: Delivered end-to-end ML capabilities for neuroscience domain and improved repository hygiene, emphasizing business value and reproducibility. Features include a CNN-based brain tumor image classifier with performance evaluation and comparison to traditional ML models, and ML education notebooks for exams and final project with setup and EDA. Additionally, repository housekeeping added metadata/config files in S04_parciales directories to standardize structure and reduce noise.
6 Commits • 3 Features
May 1, 2025May 2025 (2025-05) summary: Delivered end-to-end ML capabilities for neuroscience domain and improved repository hygiene, emphasizing business value and reproducibility. Features include a CNN-based brain tumor image classifier with performance evaluation and comparison to traditional ML models, and ML education notebooks for exams and final project with setup and EDA. Additionally, repository housekeeping added metadata/config files in S04_parciales directories to standardize structure and reduce noise.
May 2025
February 2025
1 Commits
Feb 1, 2025Feb 2025: Repository hygiene cleanup in Fernando-JAL/Neurociencias-2025-2. Removed stray .DS_Store binary file to reduce noise in diffs, prevent accidental packaging, and improve review quality. Change implemented via single, low-risk commit. This work reinforces codebase cleanliness and maintainability without impacting functionality.
February 2025
1 Commits
Feb 1, 2025Feb 2025: Repository hygiene cleanup in Fernando-JAL/Neurociencias-2025-2. Removed stray .DS_Store binary file to reduce noise in diffs, prevent accidental packaging, and improve review quality. Change implemented via single, low-risk commit. This work reinforces codebase cleanliness and maintainability without impacting functionality.
January 2025
2 Commits • 1 Features
Jan 1, 2025Month: 2025-01 — Consolidated documentation and repository hygiene for Neurociencias-2025-2. This period focused on delivering core Expectativas documentation and removing unrelated Word temp artifacts, improving clarity and readiness for reviews. Key deliverables include adding Expectativas.docx and cleaning up a temporary Word file introduced by the editor. No critical bugs were reported; minor cleanup tasks completed to ensure a clean baseline for the next sprint. The work enhances knowledge sharing and reduces onboarding time for stakeholders.
2 Commits • 1 Features
Jan 1, 2025Month: 2025-01 — Consolidated documentation and repository hygiene for Neurociencias-2025-2. This period focused on delivering core Expectativas documentation and removing unrelated Word temp artifacts, improving clarity and readiness for reviews. Key deliverables include adding Expectativas.docx and cleaning up a temporary Word file introduced by the editor. No critical bugs were reported; minor cleanup tasks completed to ensure a clean baseline for the next sprint. The work enhances knowledge sharing and reduces onboarding time for stakeholders.
January 2025
Activity
Loading activity data...
Quality Metrics
Correctness83.4%
Maintainability82.2%
Architecture82.2%
Performance75.6%
AI Usage22.2%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
CNNClassificationData AnalysisData PreprocessingData ScienceData VisualizationDeep LearningExploratory Data Analysis (EDA)Image ClassificationJupyter NotebooksKerasMachine LearningModel EvaluationRegressionScikit-learn
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline