AI PROJECTS

RECOMPY: A FRAMEWORK FOR RECOMMENDATION

Onur Boyar, Can Bulguoğlu, Oğuz Kaplan, Emre Yüksel

The participants of this project created a Python library called ‘Recompy’ which has a set of algorithms to train models. Recompy only depends on NumPy and it has all functions in order to train and test models. It has multiple similarity measures to calculate user similarities and it has special metrics to measure the performance of recommender system models.

In addition, the project also included a short demo for guests to play with during the showcase and created a website that showed recommended movies using multiple algorithms in production.

Github Repository

Medical Diagnosis Decision Support System for Parkinson's Disease

Can Bulguoğlu, Duygu Ay, Handenur Çalışkan, Orhan Ağaoğlu

For generations, assessment of speech abnormalities in neurodegenerative disorders such as Parkinson's disease (PD) has been limited to perceptual testing or user-controlled laboratory analysis based on very small human vocalization samples. However, using speech signals, detection of Parkinson's disease is now possible with the help of machine learning and deep learning methods. In this project, our aim is to detect Parkinson's disease by processing speech signals and reach the state-of-the-art level.

Furthermore, we want to investigate whether our model can achieve a generalized performance for the voice signals from different languages.

Turkish Offensive Language Detection

Abdurrahman Dilmac, Ekrem Bal, Talha Çolakoğlu, Uras Mutlu

Modern NLP tools with deep learning can be used to build a strong model that detects offensive language. Our aim is to reproduce the OffensEval 2020 benchmark on Turkish offensive language detection tasks, and then to improve the model with different techniques such as text normalization and data augmentation.

We plan to finalize the project as an open-source API so that interested people can contribute and those who need can use it in their applications or websites.