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Henush Perera's Projects

automated-essay-scoring icon automated-essay-scoring

This repository contains my solution for the Kaggle competition Automated Essay Scoring 2.0. The goal of this project is to develop an automated system capable of scoring essays based on their content and quality using machine learning techniques.

bird-sound-classification icon bird-sound-classification

This repository contains the code and methodology used for the BirdCLEF 2024 Kaggle competition, where I achieved a rank of 55th out of 974 participants, earning a bronze medal. The goal of this competition was to build a model that can accurately classify bird sounds.

chess-game icon chess-game

Developed a chess game for a specific set of requirements. Implemented functions for checkmate, stalemate, check and different classes for different pieces using Object Oriented Programming. Used test driven development approaches with over 5 test cases per function.

credit-risk-model icon credit-risk-model

Discover a comprehensive approach to constructing credit risk models. We employ various machine learning algorithms like LightGBM and CatBoost, alongside ensemble techniques for robust predictions. Our pipeline emphasizes data integrity, feature relevance, and model stability, crucial elements in credit risk assessment.

fifa-world-cup-2022-database icon fifa-world-cup-2022-database

Developed a comprehensive database for the FIFA world cup 2022, including players, coaches, staff, stadiums etc. using Google Cloud Platform (GCP), MySQL and pythonn

pii-data-detection icon pii-data-detection

This project was developed for a Kaggle competition focused on detecting Personally Identifiable Information (PII) in student writing. The primary objective was to build a robust model capable of identifying PII with high recall. The DeBERTa v3 transformer model was chosen for this task after comparing its performance with other transformer models.

portfolio-optimization-using-deep-learning icon portfolio-optimization-using-deep-learning

Thesis of my masters in Data Science. This project implements a deep learning framework applied to stock portfolio management. Using the top 20 stocks of FTSE (Financial Times Stock Exchange) top 100 by market share.

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