Deep Learning with PyTorch : Neural Style Transfer

This 2-hour-long course teaches you how to use PyTorch to implement neural style transfer. Neural style transfer is an optimization technique that takes a content image and a style picture and merges them so the output image looks exactly like the content image, but is painted in the style of a style. We will create an artistic style image from the content and the given style image. We will calculate the style and content loss function. This loss function will be minimized using optimization techniques in order to create an artistic style image that preserves style and content features. This project is designed for those who are interested in learning how to use PyTorch to implement neural style transfer. To be successful in this guided assignment, you must be familiar with the theory of neural style transfer, Python programming, and convolutional neuro networks.