December 2018
Beginner to intermediate
684 pages
21h 9m
English
Content preview from Hands-On Machine Learning for Algorithmic Trading
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CycleGAN – unpaired image-to-image translation
Supervised image-to-image translation aims to learn a mapping between aligned input and output images. CycleGAN solves this task when paired images are not available and transforms images from one domain to match another.
Popular examples include the synthetic painting of horses as zebras and vice versa. It also includes the transfer of styles by generating a realistic sample of an Impressionist print from an arbitrary landscape photo.