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You're reading from  Python Machine Learning - Third Edition

Product typeBook
Published inDec 2019
Reading LevelExpert
PublisherPackt
ISBN-139781789955750
Edition3rd Edition
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Authors (2):
Sebastian Raschka
Sebastian Raschka
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Sebastian Raschka

Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. As Lead AI Educator at Grid AI, Sebastian plans to continue following his passion for helping people get into machine learning and artificial intelligence.
Read more about Sebastian Raschka

Vahid Mirjalili
Vahid Mirjalili
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Vahid Mirjalili

Vahid Mirjalili is a deep learning researcher focusing on CV applications. Vahid received a Ph.D. degree in both Mechanical Engineering and Computer Science from Michigan State University.
Read more about Vahid Mirjalili

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Other GAN applications

In this chapter, we mainly focused on generating examples using GANs and looked at a few tricks and techniques to improve the quality of synthesized outputs. The applications of GANs are expanding rapidly, including in computer vision, machine learning, and even other domains of science and engineering. A nice list of different GAN models and application areas can be found at https://github.com/hindupuravinash/the-gan-zoo.

It is worth mentioning that we covered GANs in an unsupervised fashion, that is, no class label information was used in the models that were covered in this chapter. However, the GAN approach can be generalized to semi-supervised and supervised tasks, as well. For example, the conditional GAN (cGAN) proposed by Mehdi Mirza and Simon Osindero in the paper Conditional Generative Adversarial Nets (https://arxiv.org/pdf/1411.1784.pdf) uses the class label information and learns to synthesize new images conditioned on the provided label, that...

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Python Machine Learning - Third Edition
Published in: Dec 2019Publisher: PacktISBN-13: 9781789955750

Authors (2)

author image
Sebastian Raschka

Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. As Lead AI Educator at Grid AI, Sebastian plans to continue following his passion for helping people get into machine learning and artificial intelligence.
Read more about Sebastian Raschka

author image
Vahid Mirjalili

Vahid Mirjalili is a deep learning researcher focusing on CV applications. Vahid received a Ph.D. degree in both Mechanical Engineering and Computer Science from Michigan State University.
Read more about Vahid Mirjalili