Why do Convolutional Neural Networks work so well?

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While deep learning has existed since the 1970s, it wasn't until 2010 that deep learning exploded in popularity, to the point that deep neural networks are now used ubiquitously for all machine learning tasks. The reason for this explosion is the invention of the convolutional neural network. This remarkably simple architecture allowed neural networks to be trained on new kinds of data which were previously thought impossible.

In this video I discuss what a convolutional neural network is, why it is needed, what it can and cannot do, and why it works so damn well.

00:00 Intro
01:18 The curse of dimensionality
06:39 Convolutional neural networks
13:09 The spatial structure of images
15:06 Conclusion
  1. Algorithmic Simplicity
  2. Deep learning
  3. convolutional neural networks
  4. machine learning
  5. cnn
  6. neural network
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Комментарии
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Transformer video coming next! I'm still getting the hang of animating, but the transformer video probably won't take as long to make as this one. I haven't decided what I will do after that, so if you have any suggestions/requests for computer science, mathematics or physics topics let me know.

algorithmicsimplicity
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Please make more videos. I've been watching countless neural networks videos and until I saw your two videos I was still lost. You explained it so clearly and concisely. I hope you make more videos.

dradic
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As a physicist, I recognize this process as "real space renormalization group" procedure in statistical mechanics. So each layer is equivalent to a renormalization step (a coarse graining). The renormalization flows are then the gradual flow towards a resolution decision of the neural net. It makes the whole "magic" very clear conceptually, and also automatically points the way for less trivial renormalization procedures known in theoretical physics (not just simple real space coarse graining). The clarity of videos like yours is so stimulating! Thanks

ozachar
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Dude, your teaching style is absolutely superb! Thank you so much for these. This surpasses any of the explanations I've come across in online courses. Please make more! The way you demystify these concepts is just in a league of its own!

IllIl
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@4:17 Why is it 9^N points required to densely fill N dimensions? Where is 9 being derived from? Is it for the purpose of the example given - or a more general constraint?

ZetaReticulli
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Best video series ever, finally answering the real questions I had about HOW they do what they do, not the steps they follow

wvpohfk
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3:02 _Strictly_ speaking, there are only a finite number of images for any given image size and pixel depth, so each on can be uniquely described by a single number (and it is even an integer!). These "image numbers" cover a very, very, very wide and sparsely-filled range, but the "image number" still only has a single dimension. Thank you for the great video!

joshlevine
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This was a very cool twist in the end with the rearranged pixels. Thx, for this nice experiment.

Number_Cruncher
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Bro, you are real super man.This video gave so many deep insights in just 15 mintues providing so much strong foundation. I can confidently say, this video single handedly throwed 1000's of neural networks videos present on the internet.You raised the bar so high for others to compete.Thanks.

rohithpokala
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This is genuinely one of the best videos I have ever seen! No matter the type of content. You have somehow made one of the most complicated topic, and simply distilled it to this. Brilliant!

nananou
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This is by far the best explanation of CNNs I have ever come across. The motivational examples and the presentation are superb.

thomassynths
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The best video on CNN´s. Please make a video about V-Jepa, the proposed SSL Architecture from Yann LeCun.
Also it would be nice to have a deeper look at Diffusion Transformers or Diffusion in general.

Really really good work man!

benjamindilorenzo
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best illustrations in the subject. thank you for your work!

bassemmansour
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another superb summary and visualisation, thank you!

j.j.maverick
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This is one of the best explanations I've seen! Thanks for making videos

jcorey
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Fantastic videos.
Here before you inevitably hit 100k subscribers.

illeto
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How has the YouTube Algorithm not suggested you sooner? This is such a great video, just subscribed and keen to see how the channel explodes!

connorgoosen
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I love that you point out that we have "super human capability" because we are pre trained with assumption about the spatial information :D TLDR: "we are sucked" :D

khoakirokun
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Man, keep making more videos, this is a brilliant video

manthanpatki
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Both this and the transformers video are outstanding. I find your teaching style very interesting to learn from. And the visuals and animations you include are very descriptive and illustrative! I’m your newest fan. Thank you!

djenning
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