I just can't believe how amazing the educators are and damn !! they're providing it out here for free... Hats off to the team !!

I am a Professor and this is the best course I have found to learn about Machine learning and Deep learning....

Thank you so much MIT and instructors for making these very high quality lectures available to everyone. Students from developing countries who have aspirations to achieve something big is now possible with this type of content and information!

Over all videos on UKposts that explained about Transformer architecture (including the visual explanation) , this is the BEST EXPLANATION ever done. Simple, contextual, high level, step by step complexity progression. Thank you the educators and MIT!

Best end to the lecture: “Thank you for your attention.” ❤😂

As a CS student from University of Tehran, you guys don't have any idea how much such content could be helpful and the idea that all of this is free make it really amazing. Really appreciate it Alexander and Ava. Best hops.

One of the best lectures I have seen on Sequence Models, with crystal clear explanations! :)

This is what we need in this day and age, the teaching is amazing and can be understood by people of variable intelligence. Nice work and thanks for this course.

These are some spectacular lessons. Thank you very much for making this available.

Watching those MIT courses alongside course at my Uni in Poland, so grateful to be able to experience such a high quality education

Extremely informative, well structured and paced. A pleasure to watch and follow. Thank you.

Indeed commendable the way this lecture has been ordered and difficult topic like self-attention has been lucidly explained. Thanks to the instructors, really appreciated.

I watched and read a lot of content about Transformers and never understood what are those three Q, K, and V vectors doing so I coulnd't understand how attention works, until today when I watched this lecture doing the analogy of UKposts search and the Iron Man picture. Now it became much much clearer! Thanks for the brilliant analogies that you are making!

Thank you for this amazing content! There are many concepts discussed intuitively!

ty to MIT for giving back a little in an impactful way

Wow, Transformers, and Attention was an absolute lifesaver! 🚀🙌 The explanations were crystal clear, and I finally have a solid grasp on these concepts. This video saved me so much time and confusion. Huge thanks to the Ava for making such an informative and engaging tutorial! Can't wait to delve deeper into the world of AI and machine learning. 🤖💡

Your explanation of attention took me 2 revisits to this video to truly truly understand! But now when I did, my love for deep learning got stronger :)

These lectures are simply amazing. Thank you so much!

Came here to refresh my memory of deep learning for sequential data. I really like how Ava brings us from one algorithm to another. It makes perfect sense to me.

This is my favorite subject :) (following is self clarification of said words that feel exaggerated) 4:08 - binary classification or filtering is a sequence of steps: - new recording - retrieval of a constant record - compare new and constant record - express a property of the compare process So, sequencing really is a property of maybe all systems. While "wave sequencing" is built on top of a Sequencer System, that repeatedly uses the "same actions" per sequence element.

The most intutive explanation of Self Attention I have seen!

Just watched lecture 1, looking forward to this and the lab coming after. Thanks for this great open resource!

I am trying to step into deep learning for last couple of month. This is the best thing I have found so far. Thank you sir!.

50:30 - Attention mechnaism beautifully explained. Thank you #AvaAmini

This is incredible! Thanks a lot for this video, it’s going to help me a lot in my undergrad reasearch :)

Till Now best Course, I am doing great when I found these MIT's Lecture

Grateful for the efforts of MIT and its incredible professors delivering high quality free lectures. Filling every gap I have in my current classes ❤

Summary by Gemini: The lecture is about recurrent neural networks, transformers, and attention. The speaker, Ava, starts the lecture by introducing the concept of sequential data and how it is different from the data that we typically work with in neural networks. She then goes on to discuss the different types of sequential modeling problems, such as text generation, machine translation, and image captioning. Next, Ava introduces the concept of recurrent neural networks (RNNs) and how they can be used to process sequential data. She explains that RNNs are able to learn from the past and use that information to make predictions about the future. However, she also points out that RNNs can suffer from vanishing and exploding gradients, which can make them difficult to train. To address these limitations, Ava introduces the concept of transformers. Transformers are a type of neural network that does not rely on recurrence. Instead, they use attention to focus on the most important parts of the input data. Ava explains that transformers have been shown to be very effective for a variety of sequential modeling tasks, including machine translation and text generation. In the last part of the lecture, Ava discusses the applications of transformers in various fields, such as biology, medicine, and computer vision. She concludes the lecture by summarizing the key points and encouraging the audience to ask questions.

Amazing course! Thank you so much!

I have used LSTM and Transformer a lot, but I can still get more insights from this lecture.

15:05 we have different weights matrix for generating h_t and generating y_t h_t generated using two different weights matrix, to take contribution from previous state and current input 51:20 start of attention explanation 59:30 each attention head focus on some part similar to how each filter in cnn can learn to extract specific features like horizontal lines etc

Great Presentation @8:00 minutes it really explained a circuitry I was looking forward to exploring

She absolutely killed it. Amazing lecture(r)!

How beautifully explained. Loved it 🥰

I was searching about RNN for my Thesis work.She solved it...Nice Miss:)

Great lecture, learnt a lot. Thank you for sharing!

Thank you for this beautiful lecture.

Great Teamwork of Alex Amini and Ava Amini.

Simply brilliant!

amazing lecture series, thanks for sharing this knowledge with the world. I am curious if theres a lecture on LSTM'S

Amazing . thank you MIT.

Thank you Ava Soleimany and MIT ☺😊🤗💜

query key value pairs always put me off whener I start to learn about transformers, this time I actually finished the video. Thanks MIT

Thanks for this amazing course

I always meant to watch these lectures since 2020, but something always comes up. Now, nothing is going to stop me. Not even nothing. Great lectures, best way to learn.

Lovely presentation! It couldn't get more interesting!

This was the third video I watched in search of understanding what transformers are, and by far the best one. Thanks.

Thank you so much for the free course. Benifit and appreciate

Fully understand transformers. One of the clearest and succinct explanations out there, so intuitive. Thank you!!

What an amazing content! Thank you! ❤️

best Friday after-work fun thanks!

I already have some knowledge on the subject, however, I like to keep myself updated and there is always something new to learn. She clearly explains how what she is teaching really works. The whole video is worth watching.

Wonderful, easy to focus and understand :). Great quality! Grateful that this is open source!

Thank you for this amazing and easy to understand course! I'm a beginner of the RNN, but I can almost know all the concepts from this lecture!

I worked in spatial statistics during my graduation. And now, I think your classes will push me more and more towards the machine learning. Looking forward to apply my learning in my upcoming level of study. Thanks for your efforts 💝

Best explanation ever!!!! thank you

I come back every year to check these lectures and to see what innovations made it into the lectures. Pleasantly surprised to see the name change, congrats!

legendary lecture, thank you for sharing

I am an auditor and have very little to do with this subject, except for my curiosity. I feel lucky that these kind of videos are available for free

Finally I understand the transformer concept now. Great lecture series👍!

Thanks for sharing!

Very intuitive explanation, thanks!

Mr Amini thanks for your channel

Thank you@MIT

Wow just amazing, no words left. Really Thanks 🙏

I just started learning about RNN and LSTM especially for NLP and found this video very helpful to me. It would be really exciting if you provided a video about transformers in more depth :)

Awesome Course, Very easy to understand+++, Thx all MIT instructors 😊😊😊

Thank you for the awesome lecture

Thank you very much for this great oppurtunity to watch MIT lectures. always dreamt of a world class education and finally im doing a degree in AI and such videos are supporting my learning process very much

Great material and the best educator!. Thank you for the fantastic video! The material was not only informative but also engaging, and the quality of the presentation was top-notch. Your depth of knowledge truly shines through, making the learning experience both enriching and enjoyable. Presented such complex material with such ease. You've done an exceptional job in communicating the concepts clearly. Great work!" and everything is free! Great job MIT team!!

She is so good!!!!🎉🎉❤❤

Very good !

She is fantastic at teaching. I love how easily understandable she makes it. Thank you, Prof Amini.

Really helpful! ⭐️

This is shockingly good. Thank you.

I am 6 years old, and I have been able to follow everything said, after watching 3 times.

This is some really deep learning. MIT is the height of institutional education. 👏👏. Thanks for sharing.

Code showed at RNN Intuition chapter at 14:00 makes thing clear af. I literally said "Wow"

Thanks for sharing

I can't wait to watch

Great 👍 presentation 👏

The fact that these videos now have millions of views.... the world is evolving so fast scientifically or at least scientific culture.

Thanks for sharing such high quality content! 👌

Salutes hopr to come back MIT Deep learning. I feel you peple need to look deep inro life

This is the best lecture on UKposts! Thank you for the clear explanation. I wish you could delve deeper into the transformer architecture, though, as it was only covered in the last 15 minutes. Nevertheless, this is the most understandable video on the topic. I've watched nearly all of them, but this one stands out as the best! It would be great if you provided a more detailed explanation of transformers.

Pretty straight forward lecture.

que increible! esto es genial!

Whoever is listening to this awesome lecture I just want to say, Attention is all you need!!

Thank you so much

This is amazing. Studying from Kenya, and this absolutely is quality lectures.

perfect

Awesome Course, Very easy to understand+++

It's very helpful for me ❤

Great job simplifying very complex understanding the functions of neural networks! Avi MD MBA, MS, MHA

I've always wanted to study deep learning, but I never really knew where to start. This MIT course was my answer

Is there any videos regarding lab code implementation? I didn't found them on website. please do respond.. and of-course salute to those immensily knowledable tutors for explaining such deep topics with proper examples.

Thanks a lot!

Awsome! Video!! Very well thought out lecture. Keep rockin' !!! You just solved my problem in my NNW optimization project, in just two sentences.🤣 For 4 months, this has been driving me completely insane.💥🤣🔫 I think I'm in love.😀

Great I don't know math , but you are feeding my conceptual thoughts about life and the universe from an informational point

That's the reason why people wanted to go to the top universities such as MIT!! The explanation is so clear!!!