AabidMK/SafeBite_Infosys_Internship_Oct2024
Oct 2024 – Oct 2024
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Data AnalysisData PreprocessingData VisualizationJupyter NotebookMachine LearningMatplotlib
akshithamamidala
PROFILE
Akshithamamidala
Developed a suite of Jupyter notebooks for the SafeBite_Infosys_Internship_Oct2024 repository, focusing on end-to-end data preprocessing and visualization to support robust data analysis. Leveraged Python and Pandas to implement workflows for handling missing values, deduplication, and categorical encoding, ensuring high data quality and reproducibility. Utilized Matplotlib and Seaborn to create analytical visualizations that highlighted distributions, allergen presence, and ingredient frequencies, facilitating actionable insights for product and safety decisions. The work established a reproducible analytics pipeline, improved data readiness for stakeholder reporting, and demonstrated proficiency in notebook-based data science, with minor issues resolved to maintain workflow stability.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
19,721
Activity Months1
Your Network
6 peopleWork History
October 2024
2 Commits • 1 Features
Oct 1, 20242024-10 Monthly Summary for AabidMK/SafeBite_Infosys_Internship_Oct2024: Key features delivered, major bugs fixed, impact and accomplishments, and technologies demonstrated. Key features delivered: - Data preprocessing and visualization notebooks for SafeBite data analysis, enabling robust data cleaning (missing values handling, deduplication) and analytical visualization (categorical encoding, distributions, allergen presence, and ingredient frequencies). Major bugs fixed: - No major defects identified or fixed this month; minor issues addressed to ensure notebook execution and reproducibility. Overall impact and accomplishments: - Established a reproducible analytics workflow that accelerates data-driven insights for product and safety decisions. - Improved data quality and readiness for stakeholder reporting, reducing time to insight. Technologies/skills demonstrated: - Python, Jupyter notebooks, Pandas-based data preprocessing, data visualization, and feature analysis. Commits: - 76f4eff4afbd35a8ebf3cca5493d8116eb20cb25 (First commit) - 57e470e60004d41c19361afcc6e6715351fb9321 (Datapreprocessing.ipynb)
2 Commits • 1 Features
Oct 1, 20242024-10 Monthly Summary for AabidMK/SafeBite_Infosys_Internship_Oct2024: Key features delivered, major bugs fixed, impact and accomplishments, and technologies demonstrated. Key features delivered: - Data preprocessing and visualization notebooks for SafeBite data analysis, enabling robust data cleaning (missing values handling, deduplication) and analytical visualization (categorical encoding, distributions, allergen presence, and ingredient frequencies). Major bugs fixed: - No major defects identified or fixed this month; minor issues addressed to ensure notebook execution and reproducibility. Overall impact and accomplishments: - Established a reproducible analytics workflow that accelerates data-driven insights for product and safety decisions. - Improved data quality and readiness for stakeholder reporting, reducing time to insight. Technologies/skills demonstrated: - Python, Jupyter notebooks, Pandas-based data preprocessing, data visualization, and feature analysis. Commits: - 76f4eff4afbd35a8ebf3cca5493d8116eb20cb25 (First commit) - 57e470e60004d41c19361afcc6e6715351fb9321 (Datapreprocessing.ipynb)
October 2024
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data AnalysisData PreprocessingData VisualizationJupyter NotebookMachine LearningMatplotlibPandasScikit-learnSeaborn
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