This repository is a collection of small projects that I work on for university or out of personal interest.
Each project lives in its own folder and includes its own detailed README.
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Iris Classification KNN
A full machine learning workflow using the Iris dataset, applying K-Nearest Neighbors to classify flower species and evaluating model performance with confidence intervals and cross-validation.
Project made out of personal interest. -
Cluster–Voronoi Visualization
A geometric exploration of how k-NN (k=1) decision boundaries relate to Voronoi diagrams, using a wine dataset and high-resolution visualizations.
Project made out of personal interest. -
Optimization Using Pyomo
A linear optimization model for profit maximization across advertising channels, implemented with Pyomo and solved using GLPK.
This project was done for homework 1 of Optimization for Large-Scale Data. -
API-WorldBank
A Python client that queries the World Bank's API, focusing on data retrieval, dynamic URL construction for specific indicators and countries, and response parsing for economic analysis.
This project was lab 1 of the course Internet Contents Distribution. -
API-Creation
A foundational project implementing a custom HTTP API server in Python usinghttp.server, demonstrating data handling, query filtering, and authentication with access tokens.
This project was lab 2 of the course Internet Contents Distribution. -
BigBasket-Analysis
A basic analysis of a database collecting products, prices, and ratings from an Indian supermarket.
The goal is to predict product ratings using linear regression. -
PCA – World Happiness Index
An exploratory analysis applying Principal Component Analysis to the World Happiness dataset.
Two approaches are implemented: a manual PCA built from first principles and a PCA using the scikit-learn library.
Both methods yield equivalent results, confirming the correctness of the implementation.
For practical use and computational efficiency, the scikit-learn approach is recommended. -
Hospital Resource Optimization
A Python-based linear and integer optimization model for multi-period hospital planning, focusing on resource allocation across departments and shifts using Pyomo.
Includes analysis of primal, integer, and dual formulations to study efficiency and integrality gaps.
More projects will be added over time.