Neural Style Transfer refers to using a specific image's "style", which can be defined as color scheme and texture and applying the effects to a content image to produce an artistic image. This transformation is able to occur by giving the style image a style value and the content image a content value. The third image's goal is to minimize the difference between the style value and content value. This process is possible by integrating Machine Learning techniques. This project predominately used the Python library Pytorch to achieve these desired results.