During December 2024, Bam built an end-to-end hate speech detection workflow in the springboardmentor891v/HATE_SPEECH_DETECTION_INFOSYS_INTERNSHIP_OCT2024 repository. The project focused on developing a repeatable pipeline using Python and Scikit-learn, leveraging SVM/LinearSVC models with TF-IDF vectorization for feature extraction and robust data preprocessing. Bam established a reproducible Google Colab-based workflow, enabling rapid experimentation and rollback. The repository was structured with comprehensive documentation, clear file organization, and notebook placeholders to support future collaboration. This work provided a reusable model, an auditable evaluation process, and a clean project foundation, demonstrating depth in both engineering execution and project scaffolding.
December 2024 performance summary for the Hate Speech Detection project. Focused on delivering a repeatable, end-to-end hate speech detection workflow and establishing a solid project foundation for ongoing work. Result: reusable models, an auditable evaluation process, and a clean repository with documentation to accelerate future iterations.
December 2024 performance summary for the Hate Speech Detection project. Focused on delivering a repeatable, end-to-end hate speech detection workflow and establishing a solid project foundation for ongoing work. Result: reusable models, an auditable evaluation process, and a clean repository with documentation to accelerate future iterations.
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