Projects:
EECS 485 P4-P5: MapReduce and Web Search Engine
- Utilized Python multithreading and a MapReduce framework to build an efficient document analysis pipeline.
- Constructed an indexing API on top of document analysis results using Python Networking and Flask to quickly deliver data to a search engine frontend.
- Designed a search frontend to pull links at scale from a SQL Database using Python and Flask.
Caption: The web interface for the search model
EECS 280 P5: Machine Learning
- Built an efficient Binary Search Tree data structure using recursion for search to store values in a Map.
- Implemented a Map data structure to easily query through large datasets.
- Created a Bag of Words machine learning model to classify forum posts by category based on category word frequency.
Caption: Some of the test data ran through the model
EECS 281 P4: Pokémon Traveling Salesperson Problem (TSP)
- Engineered a Minimum Spanning Tree algorithm between a set of Pokémon nodes
- Coded a Nearest Neighbor TSP algorithm to quickly find a non-optimal TSP route between Pokémon nodes
- Devised an Optimal TSP algorithm using a Branch and Bound framework to find an optimal TSP route between Pokémon nodes
Caption: Some (cropped) optimal TSP output. The top line is total path length, the bottom line is the path between node indexes.
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