Cutting Edge Deep Learning for Coders
Other,, Summer 2018 , Prof. Jeremy Howard
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Updated On 02 Feb, 19
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.
4.1 ( 11 )
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.
In this final lesson, we do a deep dive into super resolution, an amazing technique that allows us to restore high resolution detail in our images, based on a convolutional neural network. In the process, we’ll look at a few modern techniques for faster and more reliable training of generative convnets.
We close with a look at image segmentation, in particular using the Unet architecture, a state of the art technique that has won many Kaggle competitions and is widely used in industry. Image segmentation models allow us to precisely classify every part of an image, right down to pixel level.
We hope you enjoyed your deep learning journey with us! Now that you’ve finished, be sure to drop by the forums to tell us how you’re using deep learning in your life or work, or what projects you’re considering working on now.
Sep 12, 2018
Excellent course helped me understand topic that i couldn't while attendinfg my college.
March 29, 2019
Great course. Thank you very much.