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.
After reviewing what we’ve learned about object detection, today we jump into NLP, starting with an introduction to the new fastai.text library. This is a replacement for torchtext which is faster and more flexible in many situations. A lot of today’s class will be very familiar—we’re covering a lot of the same ground as lesson 4. But today’s lesson will show you how to get much more accurate results, by using transfer learning for NLP.
Transfer learning has revolutionized computer vision, but until now it largely has failed to make much of an impact in NLP (and to some extent has been simply ignored). In this class we’ll show how pre-training a full language model can greatly surpass previous approaches based on simple word vectors. We’ll use this language model to show a new state of the art result in text classification.
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.