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Cutting Edge Deep Learning for Coders

Other,, Summer 2018 , Prof. Jeremy Howard

Updated On 02 Feb, 19

Overview

Welcome to thenew 2018 editionof fast.ai's second 7 week course,Cutting Edge Deep Learning For Coders, Part 2, where you'll learn the latest developments in deep learning, how to read and implement new academic papers, and how to solve challenging end-to-end problems such as natural language translation. You'll develop a deep understanding of neural network foundations, the most important recent advances in the fields, and how to implement them in theworld's fastest deep learning libraries, fastai and pytorch.

Includes

Lecture 6: Lesson 13: Deep Learning Part 2 2018 - Image Enhancement

4.1 ( 11 )


Lecture Details

NB: Please go to http://course.fast.ai/part2.html to view this video since there is important updated information there. If you have questions, use the forums at http://forums.fast.ai.

For the start of today’s lesson we’ll cover the CycleGAN, which is a breakthrough idea in GANs that allows us to generate images even where we don’t have direct (paired) training data. We’ll use it to turn horses into zebras, and visa versa; this may not be an application you need right now… but the basic idea is likely to be transferable to a wide range of very valuable applications. One of our students is already using it to create a new form of visual art.

But generative models (and many other techniques we’ve discussed) can cause harm just as easily as they can benefit society. So we spend some time today talking about data ethics. It’s a topic that really deserves its own whole course; whilst we can’t go into the detail we’d like in the time available, hopefully you’ll get a taste of some of the key issues, and ideas for where to learn more.

We finish today’s lesson by looking at style transfer, an interesting approach that allows us to change the style of images in whatever way we like. The approach requires us to optimize pixels, instead of weights, which is an interesting different way of looking at optimization.

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Sam

Excellent course helped me understand topic that i couldn't while attendinfg my college.

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Dembe

Great course. Thank you very much.

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