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Python Deep Learning - Second Edition
book

Python Deep Learning - Second Edition

by Ivan Vasilev, Daniel Slater, Gianmario Spacagna, Peter Roelants, Valentino Zocca
January 2019
Intermediate to advanced
386 pages
11h 13m
English
Packt Publishing
Content preview from Python Deep Learning - Second Edition

Summary

In this chapter, we introduced some new and advanced computer vision techniques. We started with transfer learning, which is a way to bootstrap network training by using pre-trained models. Next, we discussed some of the popular neural network architectures in use today. Then, we talked about capsule networks, which are a promising new approach to computer vision. After that, we moved on to tasks beyond objects classification, such as object detection and semantic segmentation. And finally, we introduced neural style transfer.

In the next chapter, we'll explore a new type of ML algorithms, called generative models. We can use them to generate new content, such as images. Stay tuned, it will be fun!

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Publisher Resources

ISBN: 9781789348460Supplemental Content