Does anyone else feel weird when he says Thank You at the end? He just gave me a free, high-quality, understandable lecture on neural networks. Man, thank *you*!

@Eigensteve

3 жыл бұрын

:) People watching and enjoying these videos makes it so much more fun to make them. So indeed, thanks for watching!

@antoniofirenze

2 жыл бұрын

@@Eigensteve ..being happy to see other people making progress. Man, you have a great heart..!

@carol-lo

2 жыл бұрын

Steve, we should be thanking "you"

@oncedidactic

2 жыл бұрын

Presenter with true class 👏

@Learner..

2 жыл бұрын

😁😍

KZread's recommendation algorithm is becoming self-aware...

@florisr9

4 жыл бұрын

It was KZread's turn in the introduction round

@GowthamRaghavanR

4 жыл бұрын

I hope Jus relu and sigmoid

@Xaminn

4 жыл бұрын

@@GowthamRaghavanR those are the safe ones

@resinsmp

4 жыл бұрын

Imagine for a second also what the algorithm never recommended to you, because it already knew you were aware.

@Xaminn

4 жыл бұрын

@@resinsmp Now that's an interesting thought haha. "Since user searched this type of topic, it must already be aware of some other certain type of topics." Simply marvelous!

I don't know why youtube decided I needed that little course, but I'm glad that it did now.

@brockborrmann2931

4 жыл бұрын

This video has common variables with other videos you watch!

@TonyGiannetti

4 жыл бұрын

Sounds like you’ve been autoencoded

@fitokay

4 жыл бұрын

That's why the CF algorithm did

@Kucherenko90

4 жыл бұрын

same thing

@user-yp6ze3dh5j

4 жыл бұрын

KZread also uses neural networks

I am addicted to your series of lectures for the last three months. your "welcome back" intro looks like a chorus to me. thank you!

You really simplify the stuff in a way that has me feel enthusiastic to learn it. Thank you.

forget neural networks, this guy figured out that it's better if you stand behind what your presenting instead of in front of it. mind blown

Steve, you are the first person I have ever seen describe an overview of neural networks without paralyzing the consciousness of the average person. I look forward to more of your lectures, focused in depth on particular aspects of deep learning. It is not hard to get an AI toolkit for experimentation. It is hard to get a toolkit and know what to do with it. My personal interest is in NLR (natural language recognition) and NLP (natural language programming) as applied to formal language sources such as dictionaries and encyclopedias. I look forward to lectures covering extant NLP AI toolkits. Sincerely, John

@pb25193

4 жыл бұрын

John, I recommend Stanford's course on recurrent neural networks. Free on KZread. It's a playlist with over 20 lectures

@pb25193

4 жыл бұрын

kzread.info/head/PLoROMvodv4rOhcuXMZkNm7j3fVwBBY42z

This is the best short intro to this topic I've seen. Thanks!

KZread is trying to teach us about itself.

@FriendlyPerson-zb4gv

4 жыл бұрын

Hahaha. Good.

@ImaginaryMdA

4 жыл бұрын

It's becoming sentient! Even worse, it's a teenager who just wants to be understood. XD

steve brunton idk who u r before watching this. but this presentation style of a glass whiteboard w/ image superimposed is the best way ive ever seen someone teach tbh. thank u at least for that. but more importantly this actually helped me understand the beast of neural nets a little more and hopefully be more prepared when our new ai overlords enslave us at least we will know how they think

Thank you, I've always seen the term neural networks generalized and always thought of it as probably a bunch of matrix operations. But now I know that there are diverse variations and use cases for them

This is a perfectly compressed overview of neural networks. What autoencoder did you use to write this?

@bunderbah

4 жыл бұрын

Human brain

@MilaPronto

4 жыл бұрын

@@bunderbah Bruman hain

@3snoW_

4 жыл бұрын

@@MilaPronto Humain bran

@mbonuchinedu2420

4 жыл бұрын

one hot encoder. lols

@mjafar

4 жыл бұрын

@@mbonuchinedu2420 That's like a robot trying to be funny

Hey I just wanted to say thank you for making this video. I found it really helpful! I particularly enjoyed your presentation format, and the digestible length. About to watch a whole bunch more of you videos! :)

This was massively helpful as an intro! When my question is just "yes but how does this ACTUALLY work", you either get pointlessly high level metaphors about it being like your brain, or jumping straight into gradient descent and all the math behind training. A+ video, thanks.

These were most productive 9 minutes. Great explanation on the architectures.

Sir your deep learning videos are the only ones on KZread I take seriously.

Awesome concise high level explanation! Thank you

Simple perfect enjoyable expaining of DNNs. Thanks for sharing!

Amazing program... I love the thing he's drawing on that projects his diagrams.

I have been looking for this content a really long time. Thanks so much.

Important note about the function operating on a node. If the functions of two adjacent layers are linear, then they can be equivalently represented as a single layer (compositions of linear transforms is itself a linear transformation and thus could just be its own layer). So, nonlinear transformations are -necessary- for deep networks (not just neural networks). That isn't to say you can't have a composition of linear transformations to compose an overall linear transformation, if there's nonlinear constraints for each operator.

Amazing video and explication , focusing on key points is very interesting for such sciences, thank you a lot and keep doing that !

Gosh i needed this intro at the start of my seminar paper...

Clear, simple, effective. Thank you!

@mrknarf4438

4 жыл бұрын

Also loved the graphic style. We're the images projected on a screen in front of you? Great result, I wish more people showed info this way

Great content for existing developers. Wow. Incredible. To say the least I am speechless. You didn’t waste my time and I appreciate that!!

Clear and concise. Thanks for posting.

Very nice. I like the autoencoders. That is basically just understanding. Intelligence is basically just a compression algorithm. The more you understand the less data you have to save. You can extract information from your understanding. That's basically what the autoencoder is about. For instance, if you want to save an image of a circle you can store all the pixels in the image, or store the radius, position and color of it. Which one takes up more space? Well, storing the pixels. We can use our understanding of the image containing a circle in order to compress it. Our understanding IS the compression. The compression IS the understanding. It's the same.

@TheMagicmagic290

4 жыл бұрын

shut up

@dizzydtv

4 жыл бұрын

profound observation

@bdi_vd3677

4 жыл бұрын

Thank you for your comment, excellent observance!

@SirTravelMuffin

4 жыл бұрын

I dig that perspective. I do think that compression can have some downsides. I feel like my emotional reactions to things are a sort of "compression". I can't keep track of everything I've read about a potentially political topic, but I can remember how it made me feel.

@PerfectlyNormalBeast

4 жыл бұрын

I like to think of autoencoder as an architect outputting a blueprint, then a construction company building that building

Excellent overview on neural network architecture. Very interesting and worthwhile video.

Best. I love your lecture. It explains problem in a simple way. Thank you so much.

I just found your channel as a suggestion from a 3Blue1Brown video. I subscribed instantly, easily explained, thanks.

@Eigensteve

Ай бұрын

So cool! Which video?

@RolandoLopezNieto

3 күн бұрын

​@@EigensteveI was watching the playlist on NN from 3Blue1Brown, and then your video appeared on my suggestions, very glad and superb content, thanks.

thank you. i somehow get inspiration from videos like these.

Thank you for your video! Seeing your example for principal values decomposition made neural networks much clearer to me than anything else I had seen till now. It allowed me to connect this to SVD-based linear modeling I used almost 10 years ago to create simplified models of visual features seen in fluid dynamics. I did not expect how much easier this suddenly seemed when it connected to what I already knew.

Amazing time spent to understand the Networks a little more.

Love your videos and your book! Can't wait to start working through it actually!

A really really great video to point out essentials of Neural Network Architecture, thanks for that video

This was most helpful, very clear, thank you

Thank you for a good explanation. This is the quality of content we want to see! 10 folds better than Siraj Raval's channel, in my opinion.

@fzigunov

4 жыл бұрын

Well, that makes sense given he's a renowned professor =)

Thank you so much for the video! The way you teach makes learning so much fun:) If you were born in ancient time, you alone would have shot the literacy rate by over 20%

I started to learn NNs in good old early 2000-s. No internet, no collegues, nor even friends to share my excitement about NNs. But even then it was obvious that the future lies with them, though I had to concentrate on more essential skills for my living. And only now, after so many years have passed, I tend to come back to NNs, cause I'm still very excited about them and it is much-much-much easier now at least ot play with them (much more powerful computers, extensive online knowlegde base, community, whatever), not speaking about career opportunities. I'm glad YT somehow guessed I'm interested in NNs, though I haven't yet searched for it AFAIR. It gives me another impetus to start learning them again. Thanks for the video! Liked and sub-ed.

Great explanation. Thank you!

Such a great explanation, thank you

Strangely enough. I needed this vid. Thank you YT ALGO

Thank you very much for this extraordinary way of teaching.

Great explanation. Thank you.

I need to watch all the videos of this channel.

Thank you so much! I needed this.

Adore this free online schooling, thanks so much Steve!!

@Eigensteve

3 жыл бұрын

Glad you enjoy it! Thanks!

One of the best introductions to AI I have seen.

@bensmith9253

4 жыл бұрын

YES. ☝️this

simply great, thanks for this intro video

Really clear. Thanks for the vidéo !

a fantastic overview thanks!!♥

Thanks for sharing Steve

Thank you for this beautiful explanation.. I really enjoy it.

Amazing video, thanks for the information

Great work on this video!

Very well explained. Thank you

So youtube know that i am currently learning neural network and this video is appear in my recommendation ,great

this is 9 minutes of pure quality education

ty YT, is all joy your latest state of recomendations

Very good explanation. 🎉

I really appreciate this talk, thank you.

Good overall neural net explanation!

Thanks for this explanation

Great explanation Thank u Sir

He Steve, thank you a lot for all your brilliant videos! One request on the topic, could you please cover how all this works with shift/rotation/scale of the image? Nobody on youtube covers this tricky part of the neuron networks used for image recognition. I keep fingers crossed that you the one who could clarify this.

Very nice explanation

Thanks, this was awesome.

I like the way of explaining by projecting on glass board....very very nice...

Could you please do a follow up on this? I basically came here for the "many many more" you mentioned towards the end. LSTMs and other architectures that are useful for time series processing. It would be nice if you could do an overview video about that class of networks.

once you get hold of the back propagation and how to do the chain rule derivatives, you understand that was not the goal! you merely opened the door, and this video is the way to your goal!

One of the most effective and useful introductory lectures on neural networks you can attend. It provides basic terminology and enables a good foundation for other lectures. HIGHLY RECOMMENDED. It would be helpful, Mr. Bunton, to say a little bit more about Neurons. Is a neuron strictly a LOGICAL function point in a process (my simple excel cell doing a logical function qualifies as a neuron with your definition), is it a PHYSICAL function point like a server, or is it both? Was there a reason you did not mention restricted Boltzmann motors? Thank you again, Sir, for the quality of this lecture.

@JorgeMartinez-xb2ks

6 ай бұрын

A neuron is pure software, a computational unit that mimics the basic functions of a biological neuron. While software relies on specific hardware for execution, a neuron is not a simple server. Unlike an Excel cell, which takes a single input and produces a straightforward output, a neuron receives multiple inputs from other neurons, processes them, and generates an output based on the combined information. Each input to a neuron is multiplied by a weight, a numerical value that represents the strength of the connection between the neurons. These weighted inputs are then summed together, and a bias value, representing an inherent offset, is added to the result. The resulting value is then passed through an activation function, which introduces non-linearity into the network's decision-making process. Activation functions, such as sigmoid and ReLU, transform the weighted input into the neuron's output, allowing the network to capture complex patterns and relationships in the data. ReLU is often used as an activation function because it requires less computational power compared to other activation functions, such as the sigmoid function. Through a process called learning, artificial neurons adjust their weights over time, enabling the network to improve its performance on a given task. Algorithms like back propagation guide this learning process, allowing the network to minimize errors and optimize its decision-making capabilities. Hope this helps.

Ok, gotta bring my notebook, thank you for the content btw

Oh wow I've been educated by your channel for a while now but did not realise you have published a textbook until your remark. Only A$80 here in Aus. Done! purchased..

Finally a good presentation

@Eigensteve

3 жыл бұрын

Thanks!

KZread recommended it. But i love it.

I love this man. You are my role model.

@Eigensteve

3 жыл бұрын

Thanks so much!

@namhyeongtaek4653

3 жыл бұрын

@@Eigensteve OMG it's my honor😯. I didn't expect you would read my comment lol. I hope I could get in to UW this fall so that I could be in your class in person.

Thank you too great video would they be building a quantum computer to be a single one of those dots to read internet transaction logs based on web page dynamics to filter and feed data across apps ?

Liked that the approach was direct and simplistic; and of course you can write your code in this manner too. So that you're not overwhelmed. Say four or five layers being coded, then you have outboard functions that handle the input and out put arrays. This last might take up most of the landscape of a program. Isn't this fellow clever? Dang. He's gotta be a Professor somewhere. Many thanks. The computer training that I had gotten was very rudimentary, first in the 60s and then another drop in the mid 90s. Luckily there's YT where you can catch up. And after a while the 'training' starts to remind you of subliminal sorts of stuff. Maybe?

Amazing good explanation and simple word for non english native speaker like me

Glad I found this channel! Loved everything about this video.

@Eigensteve

4 жыл бұрын

Glad you enjoy it!

KZread read my mind this was exactly what I was curious about

That was beautiful.

how does he write with marker on correct places if the images on the desk are virtual???

Awesome 😎... well ☺️ i didn’t understand much but i think I could use as inspiration to Spinal Cord my Dark Matter.

Thanks, Sir !

So youtube decided to make this 5 month old video famous? :D all comments are max 2h old..

@jvsonyt

4 жыл бұрын

2 days later and I'm here haha

@cyberneticbutterfly8506

4 жыл бұрын

Could easily be that some person with alot of followers shared the video. Then it has more views which makes it a more reccomended video.

@jvsonyt

4 жыл бұрын

@@cyberneticbutterfly8506 so the WHOLE system is self aware?

@cyberneticbutterfly8506

4 жыл бұрын

@@jvsonyt Hardly. It's just a trigger. Person A with a high number of followers shares a video -> They then go watch the video -> The video view number increases -> IF video has increase in X views THEN bump video ranking in reccomendations by Y amount -> You now get it in your reccomendations.

@jvsonyt

4 жыл бұрын

@@cyberneticbutterfly8506 aliens

Loved neural nets since 1998 when I read a book which showed how 3 layer nets can solve difficult problems. In the 21st century the neural nets are magnificent and a credit to the brains of the human race. I am using a 21st century neural net myself and it's great. Hahahaha. Great video

Ok, thank you.

youtube recommendation system (powered by neural network?) brought us here..

@matt-stam

4 жыл бұрын

"Thanksgiving? Nah, neural network time" -KZread

@Vasharan

4 жыл бұрын

AI using humans to improve AI. Clever girl.

@klodianelshani7708

4 жыл бұрын

@@Vasharanthey have become sneakily clever xD

beautiful! thanks.

Amazing. Thank you :)

Thank you is all I can say but it doesn't feel like enough for this

Thanks for your explanation in the video. have learned a lot. Am doing research in speech emotion recognition. Can you pls tell me the best Deep learning algorithms that will work?

Thanks

I really really really like the way you present- could you help me understand your set up? There's a see-through glass that you draw on, there's a projector (i think) that's allowing you to see which part of the presentation you're in. Plus the dark shirt enables me to just focus on your face, and your hands. It's a very intuitive interface for learning. Your hand gestures easily capture my eyes' attention. Do please elaborate. Thanks!

Beautiful

Thank you!

Thank you Very much

Steve: nice talk,... many questions come up, I'll ask a few 1)Do you distinguish planar vs non-planar networks? 2)Do RNN(s) become unstable? They look like control system time dependent processes. 3)Has anyone applied Monte Carlo toward selection of topology of a NN, or toward the activation function selection,...? Fascinating area to study.

Damn good video never knew I needed it but damn. Thanks

@Eigensteve

4 жыл бұрын

Thanks!