Visual Guide to Transformer Neural Networks - (Episode 3) Decoder’s Masked Attention

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Visual Guide to Transformer Neural Networks (Series) - Step by Step Intuitive Explanation

Episode 0 - [OPTIONAL] The Neuroscience of "Attention"

Episode 1 - Position Embeddings

Episode 2 - Multi-Head & Self-Attention

Episode 3 - Decoder’s Masked Attention

This video series explains the math, as well as the intuition behind the Transformer Neural Networks that were first introduced by the “Attention is All You Need” paper.

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References and Other Great Resources
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Attention is All You Need

Jay Alammar – The Illustrated Transformer

The A.I Hacker – Illustrated Guide to Transformers Neural Networks: A step by step explanation

Amirhoussein Kazemnejad Blog Post - Transformer Architecture: The Positional Encoding

Yannic Kilcher Youtube Video – Attention is All You Need
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Correction in the Video: A huge shout-out to @jackzead "What comes out of the encoder should be the key and value matrix and what comes out of the bottom part of the decoder is the query matrix."

*TIMESTAMPS*
Here are the timestamps associated with the concepts covered in this video:
0:00 – Recaps of Parts 1, 2
0:52 – Residual Connections
4:25 – Transformer Decoder
9:52 – Decoder's Masked Attention

HeduAI
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These explanations are so good that they should be included into Tensorflow's and PyTorch's documentations, seriously !

LeManneCris
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This series deserves so much more "attention"

dy
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You are the mother of StatQuest and 3Blue1Brown. Both of these guys are awesome in explaining complex ideas in simple words. But you are the best.

ahp-
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I have tried to learn transformer from various sources with several attempts in the past a couple of months, but I couldn't get the gist of it. I wish I have spotted your 3 episodes earlier, they were extremely helpful and easy to follow.

I really appreciate the time, effort, love and joke you put into your videos, and sincerely wish you could keep making these types of videos on DL topics. I love the fact that each concept/technique is well explained with a concrete example as well as why it was done this way not the others.

You are truely gifted at explaining complicated concept for people with limited DL background. Please keep up the good work

alsonyang
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This is one of the best explanations I've ever seen. Thank you so much!

SaurinShah
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Please make series of NLP, Deep Learning. Your teaching style is amazing.

pratikpratik
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You have an amazing gift of explaining complex things in an intuitive way!

ankoor
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it hurts that ur skills are so under-rated, the ai community needs more of you!

rrxcihr
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Literally THE best 3 video playlist 👌👌

rajarshideeplearning
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havn't seen such a good series of vids in a realy long time

whitelady
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Super clear explanations. Really appreciate you putting this series together! (and love the pop culture references)

jb_kc__
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this is my 3rd comments for my entire life using Youtube! The best video for explaining transformer! Hope you will make more videos in future!

weihongchin
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Her way of explaining is so crystal clear. Its very evident she is a genius

azerioauditore
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You are my savior. Went through a bunch of videos yesterday, didn't understand shit.. finally found these awesome short 3 videos today.

SaiGopalCAP
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Batool you are really a great teacher. Thanks for the content. Please provide more vid on LLMS and AI

maysammansor
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This is a great playlist and one of the best I have come across for transformers.
Thanks!
And looking forward to your next set of videos.

prajwalanagani
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You are truly truly gifted in explaining very technical topics in an intuitive way! I often get embarrassed to go to YouTube to learn about DL concepts considering that I have studied the topic for a couple years now, but in all honesty, the scientific community desperately needs people like you. Thank you for investing your time in making the world a better place!

royeyono
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Thank you for all your videos about transformers. They are incredible. It's obvious you've worked hard on them, and they've been really instructive.

benak
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This was an amazing mini series. Well done!

jonasmanuel