Neural Network
supervised machine learning // python // numpy + pytorch // decision boundaries
A neural network project implementing a perceptron from scratch and training multi-layer models on synthetic datasets with visualized decision regions.
This project is an exploration of neural networks, where I implemented a perceptron from scratch and trained multi-layer neural networks on synthetic datasets. I experimented with different architectures, visualized decision boundaries, and compared model performance on increasingly complex patterns such as linearly separable data and the Two Moons dataset.