Taha Humayun
CS student turning Python, AI & automation into solutions
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Developed an autonomous delivery robot simulation using AI pathfinding algorithms including A*, BFS, and DFS to navigate dynamic grid environments. Built an interactive GUI to visualize robot movement, obstacle detection, and optimal path selection in real time. Integrated heuristic-based decision-making to handle multiple delivery targets and route optimization. This project demonstrates practical application of AI search algorithms and GUI development in Python.
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Implemented AI automation for my Youtube channel.
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Built a full-featured exam scheduling and management system with a graphical user interface in Python. Supported student registration, exam timetable generation, result entry, and grade report generation. Implemented file-based data persistence and user authentication for both admin and student roles. Focused on clean system design and a user-friendly interface for real-world usability.
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Implemented a multi-layer perceptron from scratch using the Perceptron Training Rule and Gradient Descent Delta Rule without using any ML libraries. Trained the network over multiple epochs with numerical weight updates and convergence tracking. Demonstrated deep understanding of forward propagation, error calculation, and weight adjustment. This project reflects strong theoretical and practical knowledge of how neural networks learn.
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