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Headphones on, close the curtains, set the mood, sit back and just take it all in.
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SECOND CHANEL:
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PATREON:
You can help support my videos here, everything goes towards making better and more videos and is massively appreciated! https://www.patreon.com/carswithluke
WHERE IS MY MUSIC FROM?
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#PaperExplained #PaperReview
Paper: https://arxiv.org/abs/1810.04805
Useful resources to learn about transformers:
https://peterbloem.nl/blog/transformers
https://nlp.seas.harvard.edu/2....018/04/03/attention.
https://jalammar.github.io/ill....ustrated-transformer
Useful resources to learn about BERT:
https://jalammar.github.io/illustrated-bert/
In this video we go through how to code the GoogLeNet or InceptionNet from the original paper in Pytorch. I explain how the network works in the first couple of videos and then how to implement it from scratch.
Paper:
https://arxiv.org/abs/1409.4842
People often ask what courses are great for getting into ML/DL and the two I started with is ML and DL specialization both by Andrew Ng. Below you'll find both affiliate and non-affiliate links if you want to check it out. The pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
ML Course (affiliate): https://bit.ly/3qq20Sx
DL Specialization (affiliate): https://bit.ly/30npNrw
ML Course (no affiliate): https://bit.ly/3t8JqA9
DL Specialization (no affiliate): https://bit.ly/3t8JqA9
GitHub Repository:
https://github.com/aladdinpers....son/Machine-Learning
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PyTorch Playlist:
https://www.youtube.com/playli....st?list=PLhhyoLH6Ijf