springboardmentor891v/HATE_SPEECH_DETECTION_INFOSYS_INTERNSHIP_OCT2024
Dec 2024 – Dec 2024
1 Month active
Languages Used
CSVJupyter NotebookPython
Technical Skills
Data CleaningData IngestionData PreprocessingData VisualizationMachine LearningNLTK
SANJAY VENKATESHWARAN
PROFILE
Sanjay Venkateshwaran
Sanjay developed a hate speech detection model for the springboardmentor891v/HATE_SPEECH_DETECTION_INFOSYS_INTERNSHIP_OCT2024 repository, focusing on robust text classification using Python and scikit-learn. He implemented data preprocessing and upsampling to address class imbalance, then built a pipeline leveraging SGDClassifier and TF-IDF for feature extraction. The model achieved a strong F1 score, supporting reliable content moderation. Sanjay also maintained repository hygiene by removing placeholder and temporary files, ensuring a clean and accessible codebase. He contributed formal documentation to facilitate knowledge transfer and compliance. His work demonstrated depth in data cleaning, natural language processing, and disciplined version control practices throughout the project.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
7Total
Bugs
1
Commits
7
Features
2
Lines of code
101,354
Activity Months1
Work History
December 2024
7 Commits • 2 Features
Dec 1, 2024Concise December 2024 monthly summary for springboardmentor891v/HATE_SPEECH_DETECTION_INFOSYS_INTERNSHIP_OCT2024. Delivered a hate speech detection model with preprocessing, upsampling for class imbalance, and a text classification pipeline using SGDClassifier. The model was trained and evaluated with a strong F1 score, demonstrating a robust moderation capability. Performed repository housekeeping to remove placeholder and temporary files, maintaining a clean, onboarding-friendly codebase. Added formal documentation (DOCUMENTATION OF INFOSYS.pdf) to support knowledge transfer and compliance. Technologies demonstrated include Python, scikit-learn, data preprocessing, upsampling, model evaluation, and Git-based version control. Business value centers on faster iteration cycles, improved content moderation reliability, and clearer documentation for interns and stakeholders.
7 Commits • 2 Features
Dec 1, 2024Concise December 2024 monthly summary for springboardmentor891v/HATE_SPEECH_DETECTION_INFOSYS_INTERNSHIP_OCT2024. Delivered a hate speech detection model with preprocessing, upsampling for class imbalance, and a text classification pipeline using SGDClassifier. The model was trained and evaluated with a strong F1 score, demonstrating a robust moderation capability. Performed repository housekeeping to remove placeholder and temporary files, maintaining a clean, onboarding-friendly codebase. Added formal documentation (DOCUMENTATION OF INFOSYS.pdf) to support knowledge transfer and compliance. Technologies demonstrated include Python, scikit-learn, data preprocessing, upsampling, model evaluation, and Git-based version control. Business value centers on faster iteration cycles, improved content moderation reliability, and clearer documentation for interns and stakeholders.
December 2024
Activity
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Quality Metrics
Correctness68.6%
Maintainability68.6%
Architecture68.6%
Performance68.6%
AI Usage25.8%
Skills & Technologies
Programming Languages
CSVJupyter NotebookPython
Technical Skills
Data CleaningData IngestionData PreprocessingData VisualizationMachine LearningNLTKNatural Language ProcessingPandasSGDClassifierScikit-learnTF-IDFText Classification
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