For details and code on building a translator using a transformer neural network, check out my playlist "Transformers from scratch": th-cam.com/video/QCJQG4DuHT0/w-d-xo.html
I have studied for several years AI, NPL and Neural networks. But the way you explained this was lovely, friendly and very simple which is why I am pretty sure you are BERT
I'm honestly amazed of how you managed to transform a complex algorithm in a simple 10 minutes video. Much thanks to you, my final thesis appreciates you.
I read many blogs on BERT but they were more focused on how to use BERT rather than what actually BERT is?. This video helped me clear all my doubts regarding how Bert is trained. Clear and concise explanation.
Best explanator on youtube, you have a good mix of simplifying so it can be understood, but not overly simplifying so we learn deeply enough. The idea of having 3 passes going deeper was a great idea as well.
Excellent Explanation. Main thing to note is the finer point around explanation/mention of the loss functions that BERT uses. As not many other videos on same topic cover this. Tood Good
dude , you are amazing , you explained the state of the art NLP model , in such a well explained and concise video . Thanks a ton for this video !!!!!!
After reading lot of blogs, videos, I understood its so difficult network. But after going through this, I feel so easy to understand BERT(and its varient available in transformer library)
Amazing stuff. For visualization purposes, when you get into a deeper pass, I would recommend always adding the zooming effect for intuitive understanding. I am not sure about others, but when you do that, I instantly know "OK, now we are within this 'box' "
The NSP task does not directly involve bidirectional modeling in the same way as masked language modeling (MLM) does. Instead, it serves as a supplementary objective during BERT's pre-training phase. The purpose of the NSP task is to help the model understand relationships between sentences and capture broader context beyond adjacent words.
At 7:55 , the position embeddings as said in the video encodes the position of a word in a sentence. But in the slide, the sequence of position embeddings if E0..E5,E6,E7..E10 instead of E0..E5,E0,E1..E5 (implying position embedding of a word depends on how the 2 sentences are arranged)
Im a teacher with a compi-sci masters and am just diving into AI. This was absolutely great! I studied natural language in college about 20 years ago and this video really helped form a mental bridge with the new technologies. Language chatbots have been around forever!and the ones I studied used Markov chains that used small corpuses. So of course students would dump porn novels, the bibel and whatnot into it and then start it talking. We never laughed so hard!
I always watch your videos and appreciate the efforts you put to make the complicated topics so easy and clear. Thankyou for all your work. I really like the way you explain in 3 passes.... great work
For details and code on building a translator using a transformer neural network, check out my playlist "Transformers from scratch": th-cam.com/video/QCJQG4DuHT0/w-d-xo.html
I have studied for several years AI, NPL and Neural networks. But the way you explained this was lovely, friendly and very simple which is why I am pretty sure you are BERT
Just watched a video on Transformers, and now this. Am astounded at how you explained such complex notions with such ease!
Hugely underrated channel!
Thanks a lot! Glad you liked it 😊
Amazing Explanation :)
big fan sir
hear hear! so agree!
To teach us , you study and explore .. really grateful for your efforts Krish .
Where there is krish sir... I will come there. .... Sir I found u here also...
We are learning together 😇
Nice to meet you sir
Thanks for the great explanation of Transformers and the architecture of BERT.
My pleasure and thank you for the super thanks :)
I'm honestly amazed of how you managed to transform a complex algorithm in a simple 10 minutes video. Much thanks to you, my final thesis appreciates you.
Hahaha anytime ):
I read many blogs on BERT but they were more focused on how to use BERT rather than what actually BERT is?. This video helped me clear all my doubts regarding how Bert is trained. Clear and concise explanation.
Don't hesitate, this is the best video of BERT explanation for sure!
OMG!!!! This vid is a life-saver! just elucidated so many aspects of NLP to me (a 3 month beginner who still understands nothing
Phenomenal the way you condense such a complicated concept into a few minutes, clearly explained.
Thanks so much for the compliments:)
I wish I had come across this channel earlier. You have a wonderful skill in explaining complicated concepts. I love your "3 pass" approach!!
Dude this video is incredible. I cannot express how good you are at explaining
Thanks for watching! Super glad it is useful
Good try though!
The BEST explanation on BERT. Simply outstanding!
Every time I watch this video I gain a better understanding of the procedure. Thanks a lot for the great content!!!
Anytime! Look forward for more
Always come back to your explanation whenever want to refresh bert concepts. Thanks for the effort.
Thanks for the super kind words :)
I love the "pass1" "pass2" concept of how you explain things. It's great.
Best ever explanation of BERT! Finally understood how it works :)
Do you realize you are the only good description of how exactly fine tuning works I have found, and I've been researching for months. Thank you!!!
You are too kind. Thank you for the donation. You didn’t have to bug it is appreciated. Also super glad this content was useful! More of this to come
Wow.. just switched from another BERT explained video to this.. stark difference.. excellent explanation indeed.. thanks..
Best explanator on youtube, you have a good mix of simplifying so it can be understood, but not overly simplifying so we learn deeply enough. The idea of having 3 passes going deeper was a great idea as well.
God Level Explanation. Thanks Man !
This is one of the best resources explaining BERT available online.
Extremely underrated channel, didn't find any other good explanation on TH-cam/Medium/Google
Excellent Explanation. Main thing to note is the finer point around explanation/mention of the loss functions that BERT uses. As not many other videos on same topic cover this. Tood Good
Thanks so much :)
Was struggling to understand the basics of BERT after going through Transformer model. This video was indeed helpful.
this must be one of the best explanation videos on the internet, thank you!
You are very welcome :)
I am very impressed by the clarity and core focus of your explanations to describe such complex processes. Thank you.
You are very welcome. Thanks for watching and commenting :)
dude , you are amazing , you explained the state of the art NLP model , in such a well explained and concise video . Thanks a ton for this video !!!!!!
You are super welcome. Thanks so much for commenting this!
Wow , Best Explanation on BERT present in TH-cam that too Free, Thanks Man you made NLP easy.🍺
Glad! Thanks a ton for watching
After reading lot of blogs, videos, I understood its so difficult network. But after going through this, I feel so easy to understand BERT(and its varient available in transformer library)
Very very friendly, clear and masterful explanation. This is exactly what I was after. Thank you!
One of the best videos on BERT.
Great work!
Wishing you loads of success!
Thank you for the explanation. You really have a knack for explaining NLP concepts clearly without losing much fidelity. Please keep posting!
Amazing stuff. For visualization purposes, when you get into a deeper pass, I would recommend always adding the zooming effect for intuitive understanding. I am not sure about others, but when you do that, I instantly know "OK, now we are within this 'box' "
Good thought. I'll try to make this apparent in the future. Thanks!
Nice job, man! Especially the multi-phase approach of explaining things, top to bottom.
Super happy you liked the approach. Thanks for commenting
First half is exactly how much I need to understand right now, thank you :)
Awesome! You are very welcome!
The one which I was looking for the past 6 months.! Thanks a lot for making this.
I'm late. But. Here now!
The multiple passes of explanation is an absolutely brilliant way to explain! Thanks man.
I've read 4 articles before coming here. Couldn't connect the dots. This single video showed me the way.. Thanks a lottt
Super glad it helped :)
Simple and clear explanations (which shows you know what you're talking about). And cool graphics. Will be back for more videos :)
Thanks! Keep tuning in!
3 pass explanation is a really good approach to explain this complex concept. Best video on BERT
Great video! But what is pass 1, pass 2 and pass 3?
That's it. The best explanation i came through. Receive my upvote and subscription 😁
Many thanks. Join the discord too :3
Best Explanation by far!
Excellent explanation!. Will never miss a video of yours from now on!
Excellent introduction, visualizations and step by step approach to explain this. Thanks a ton.
You are oh-so welcome. Thank you for watching and commenting:)
Thank You. Love from India.
Great explanation, I really like the three pass idea it breaks down a lot of complications to simple concepts.
Very nice high level understanding of Transformers...
Excellent Explanation! Thank you!
Best explanation i have seen so far on BERT.
I thank you kindly ;)
wow AMAZING EXPLAINATION. Thank you very much
Thank you so much for the clear explanation, I get the grip of the BERT now!
thank you so very much! one video was enough to get the basics clear
Glad! Welcome!
Wow, thanks!! I tried watching many videos and couldn't understand a single thing. But yours was truly concise and informative.
loved your explanation bro, earned yourself a sub
BEST EXPLAINATION EVEERRRR
Probably the best (easiest to understand in one go) video on BERT. Thanks ❤️
The NSP task does not directly involve bidirectional modeling in the same way as masked language modeling (MLM) does. Instead, it serves as a supplementary objective during BERT's pre-training phase. The purpose of the NSP task is to help the model understand relationships between sentences and capture broader context beyond adjacent words.
Excellent and concise explanation. Loved it. Thanks for this fantastic video.
Your Videos are very well explained !
Amazing Explanation! I am speechless :)
Beautiful explanation!
Thanks for wonderful explanation for bert architecture 🍀🌹
This is amazing! Crystal clear explanation, thanks a lot.
Well explained! I have been looking for something like this for quite long!
Omg your videos are so good! So happy I found your channel, I'm binge watching everything :D
Glad you found my channel too! Thank you! Hope you enjoy them!
Well explained. Short and to the point
At 7:55 , the position embeddings as said in the video encodes the position of a word in a sentence. But in the slide, the sequence of position embeddings if E0..E5,E6,E7..E10 instead of E0..E5,E0,E1..E5 (implying position embedding of a word depends on how the 2 sentences are arranged)
thank you for sharing the video! very clear and helpful!!
@11:08 Please go on forever :):D... the best explanation I have seen so far, Thanks man!
Fantastic explanation, Covered each and every point in the BERT.
Looking forward for more videos on NLP.
Im a teacher with a compi-sci masters and am just diving into AI. This was absolutely great! I studied natural language in college about 20 years ago and this video really helped form a mental bridge with the new technologies. Language chatbots have been around forever!and the ones I studied used Markov chains that used small corpuses. So of course students would dump porn novels, the bibel and whatnot into it and then start it talking. We never laughed so hard!
Such a underrated channel. Keep it up man
This is an excellent summary. Very clear and super well organized. Thanks very much
Thank you so much for watching ! And for the wonderful comment :$
Good touch to put the references on the description instead of on the slides
So simple and easy to understand, thanks a lot
Super glad this was useful :)
Excellent articulation of the concept. Thank you.
Very good explanation, Easy to understand! Come on!
great video, i like the 3-pass method you used to explain the concepts
No one explains DL models better than this guy.
Great Video! So easy to follow!
Not bad! Loved the video. Please add a little bit of more explanation for upcoming vids if preferrable.
I always watch your videos and appreciate the efforts you put to make the complicated topics so easy and clear. Thankyou for all your work. I really like the way you explain in 3 passes.... great work
Loved how you explained BERT really well. Great job!
Wow I've just discovered your channel, it's full of resources, very nice!
great explanation, I understood everything ! thanks a lot
Thanks so much for watching and commenting :)
Your videos are great! Amazing work
Hey, your explantation and presentation on complicated concepts made me clear about TF and BERT.
I will expect you to upload more exciting videos.
awesome introduction to a very challenging topic
Thank you. Uploading a related video on this soon too :)
No more reading after this. Loved IT. 😊
Many thanks 😊
Big Big Thanks to make such awesome Videos..
very good explanation! thank you!
Wonderful, and the best explanation of BERT ever :) , Good Job , and big thank you !
Thanks a bunch for these wonderful videos!
Thanks for explaining this in such a simple way :)
This explanation is pretty amazing! I have a presentation on this soon. Thank you so much!
Hey this is an exceptional training video.
Thanks man! Great work!
Thank you so much for these videos.
You are welcome! Thanks so much for commenting! Really appreciate it :)
new subscriber, amazing explanation!