Neural Style Transfer is a technique in computer vision that combines the content of one image with the style of another. It uses deep learning algorithms, particularly convolutional neural networks (CNNs), to analyze and extract features from both images. The result is a new image that retains the original content while adopting the artistic style of the second image. This process has gained popularity in art and design, allowing users to create unique artworks by merging photographs with the styles of famous artists like Vincent van Gogh or Pablo Picasso. Neural Style Transfer has applications in various fields, including digital art, photography, and even video production.