Created a hybrid machine learning model combining techniques ranging from random forests to neural networks with unsupervised learning. Built on the MovieLens 100K dataset, the system recommends movies by analyzing user preferences, history, and similarities with other users.

Technologies used: Python, Scikit-learn, and Pandas.

Movie Recommender

Designed an AI system in Unity using ML Agents to simulate the behavior of ants. The project utilizes agent-based modeling and sensors to create realistic and adaptive ant-like actions.

Technologies used: Unity, ML Agents.

Ant

Coming soon...

Text-to-Speech Audiobooks

Development of a neural network model capable of converting text into speech, aimed at creating audiobooks.