December 2019
Intermediate to advanced
468 pages
14h 28m
English
Content preview from Advanced Deep Learning with Python
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Summary
In this chapter, we discussed how to create new images with generative models, which is one of the most exciting deep learning areas at the moment. We learned about the theoretical foundations of VAEs and then we implemented a simple VAE to generate new MNIST digits. Then, we described the GAN framework and we discussed and implemented multiple types of GAN, including DCGAN, CGAN, WGAN, and CycleGAN. Finally, we mentioned the neural style transfer algorithm. This chapter concludes a series of four chapters dedicated to computer vision and I really hope you've enjoyed them.
In the next few chapters, we'll talk about Natural Language Processing and recurrent networks.
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.