During my time in San Francisco, we created World Schedule. A Meeting Planer that connects people over diffrent timezones. It immediatly played out played to be useful.

I built a deep learning model to classify brain tumors on MRI scans. By achieving high accuracy (up to 99%) and visualizing results with Grad-CAM, this project demonstrates how AI can contribute to early detection and diagnosis in healthcare. This project can assists neurologist in real life.

During my time in San Francisco, I worked on the Apple Vision Pro. Coming soon...

I did research on Explainable Artifical Intelligence (XAI). Concret on methods to make advanced AI models more transparent and understandable. As AI models became too complex for humans to comprehend, it is essential that we remain having trust in these models. My study compares two key techniques (LIME & GradCAM) for explaining how Deep Convolutional Neural Networks form decisions.

I recreated Andrej Karpathy’s NanoGPT from scratch to dive deep into the mechanics of Large Language Models (LLMs) and transformers. This hands-on project allowed me to understand how LLMs generate human-like speech on the most fundamental level.

I built a 2D Platformer game using Pygame.

I implemented the Backpropagation algorithm from scratch to understand how neural networks on the most fundamental level.

I applied GradCAM on the classical MNIST Digit Recognition Problem to visualize most influential features for model decision.

I have some notebooks on the Hands-on ML book.

I built an autonamous Agent to land the Lunar Lander using Gymnasium API and Stable Baselines3, implementing the DQN algorithm.

I developed a strategy game with a team of four people using Maven.

I did a project on the Prisoner's Dilemma to analyze which strategies work best in game theory. This project can be applicable in real life strategic situations.