This chapter presented a very novel technique in the deep learning landscape, leveraging the power of deep learning to create art! Indeed, data science is an art as well as a science of using data in the right way, and innovation is something that drives that. We covered the core concepts of neural style transfer, how to represent and formulate the problem using an effective loss function, and how to leverage the power of transfer learning and pretrained models like VGG-16 to extract the right feature representations.

The field of computer vision is ever evolving, and deep learning coupled with transfer learning has opened up doors for innovation and building novel applications. The examples in this chapter should help you appreciate the vast scope of novelty in this field, and enable you to get out there and try new techniques, models, and methods to build systems like neural style transfer! Coming up, more interesting and complex case-studies around image captioning and colorization. Stay tuned!