প্রজেক্ট
Unix Shell (C)
custom shell with pipes, redirection and command history.
Basit IbrahimBRAC University
BRAC University-এর শিক্ষার্থীদের প্রজেক্ট, লেখা, গবেষণা ও কার্যক্রম।
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custom shell with pipes, redirection and command history.
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end-to-end ML workflow with preprocessing, linear regression and evaluation metrics.
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social-impact crowdfunding web application.
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built and trained CNN models, covering data preprocessing, architecture design and evaluation.
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Designed a fan-focused website using Google Sites, featuring FC Barcelona news, player profiles, club history, multimedia content, and football merchandise promotions to engage supporters in Bangladesh.
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Conducted a qualitative research study titled “Financial Transaction Reconciliation and Process Coordination at Bangladesh Bank: Key Factors to Financial Supply Chain Management,” focusing on financial reconciliation, interdepartmental coordination, and o
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P Rodela (2023), ‘uncertain love’, Resonance, Vol 6, pg 23-24
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P Rodela (2023), ‘it is a curse: period!’, Resonance, Vol 5, pg 82
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Compared Logistic Regression, Decision Tree and KNN (Python).
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Document-based database with CRUD operations (MongoDB).
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7-table database (2NF), redesigned ERD, 12 analytical queries.
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Journal entries, invoices, P&L and Balance Sheet (QuickBooks).
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Cleaned 1,193 rows and built an interactive KPI dashboard (Excel, Power BI).
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Developed an end-to-end machine learning pipeline using Python,Pandas,Matplotlib to classify food delivery speeds across multiple models, achieving 78% accuracy and 0.92 ROC-AUC with Logistic Regressi
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Manging parking spots using mern stack and mongo db.
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Built a 3D exploration game using OpenGL, implementing custom navigation algorithms and enemy patrol AI logic and Applied advanced logic-building to optimize rendering performance
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Designed a web-based management system, utilizing MongoDB to engineer efficient database schemas for structured data storage and retrieval and Leveraged Git/GitHub for version control.
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Built a machine learning model to classify software quality using complexity, churn, bugs, testing, and developer-experience features. Preprocessed 1,600 records and compared multiple classification algorithms using standard evaluation metrics.