TCS-2021/Data-Mining-Project
Mar 2025 – Mar 2025
1 Month active
Languages Used
CSVPython
Technical Skills
Data MiningData VisualizationPandasPythonSequential Pattern MiningStreamlit
SherinJA
PROFILE
Sherinja
In March 2025, Jasherin developed an end-to-end sequential pattern mining feature for the TCS-2021/Data-Mining-Project repository. She implemented the core Generalized Sequential Patterns (GSP) algorithm in Python using Pandas for data handling, enabling users to mine frequent sequences from CSV datasets. To streamline the workflow, she built an interactive Streamlit interface that allows CSV upload, minimum support configuration, and tabular visualization of results. This integration eliminated the need for manual scripting, making data mining accessible to non-technical users. The work demonstrated depth in algorithm implementation and user interface design, though it focused on feature delivery without addressing bug fixes.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
401
Activity Months1
Your Network
20 people
Work History
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary highlighting key feature delivery, bug status, impact, and skills demonstrated for business performance reviews.
2 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary highlighting key feature delivery, bug status, impact, and skills demonstrated for business performance reviews.
March 2025
Activity
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Quality Metrics
Correctness85.0%
Maintainability80.0%
Architecture80.0%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSVPython
Technical Skills
Data MiningData VisualizationPandasPythonSequential Pattern MiningStreamlit
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