This repository implements neural style transfer, a technique that extracts the artistic style from one image and applies it to the content of another image. It uses a VGG-based neural network to separate and recombine content and style, optimizing an output image using TensorFlow’s automatic differentiation and the Adam optimizer. The project generates artistic images by minimizing a content loss and a style loss computed from intermediate neural network layers.