Home page: https://www.3blue1brown.com/
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Full playlist: http://3b1b.co/neural-networks
Typo correction: At 14:45, the last index on the bias vector is n, when it’s supposed to in fact be a k. Thanks for the sharp eyes that caught that!
For those who want to learn more, I highly recommend the book by Michael Nielsen introducing neural networks and deep learning: https://goo.gl/Zmczdy
There are two neat things about this book. First, it’s available for free, so consider joining me in making a donation Nielsen’s way if you get something out of it. And second, it’s centered around walking through some code and data which you can download yourself, and which covers the same example that I introduce in this video. Yay for active learning!
https://github.com/mnielsen/neural-networks-and-deep-learning
I also highly recommend Chris Olah’s blog: http://colah.github.io/
For more videos, Welch Labs also has some great series on machine learning:
For those of you looking to go *even* deeper, check out the text “Deep Learning” by Goodfellow, Bengio, and Courville.
Also, the publication Distill is just utterly beautiful: https://distill.pub/
Lion photo by Kevin Pluck
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Animations largely made using manim, a scrappy open source python library. https://github.com/3b1b/manim
If you want to check it out, I feel compelled to warn you that it’s not the most well-documented tool, and has many other quirks you might expect in a library someone wrote with only their own use in mind.
Music by Vincent Rubinetti.
Download the music on Bandcamp:
https://vincerubinetti.bandcamp.com/album/the-music-of-3blue1brown
Stream the music on Spotify:
If you want to contribute translated subtitles or to help review those that have already been made by others and need approval, you can click the gear icon in the video and go to subtitles/cc, then “add subtitles/cc”. I really appreciate those who do this, as it helps make the lessons accessible to more people.
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3blue1brown is a channel about animating math, in all senses of the word animate. And you know the drill with YouTube, if you want to stay posted on new videos, subscribe, and click the bell to receive notifications (if you’re into that).
If you are new to this channel and want to see more, a good place to start is this playlist: http://3b1b.co/recommended
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When you weight between 0 and 1, I'm seeing an analogy to quantum theory. Are there models that make a difference on discreteness of weights? Is a "quantized" weight the very definition of the artificial in artifical/cylon intelligence opposed to natural/human intelligence?
now I'm glad I took calculus
You remind me of why I loved learning
Are you a god am I in the heaven
Or this some high tech mit lecture going on. YouTube give him applause ? ?
You're my HERO!
Stuff like this is a great insight to how the human brain can have things like optical illusions.
Hi great video and highly informative. I am currently studying Neural Networks and have written my own Neural Network in Java. However, I wish to take it to the next level and implement image recognition.
My question is: how can I obtain the grayscale value from a single pixel?
if RELU is simpler and quicker than Sigmoid so why are we learning sigmoid function in this video?
This video is amazing. Thanks a lot. You managed to show it better in 20 minutes than MIT videos in 40.
wonderful explanation!
Good job and very helpful
Best explanation of the concept of deep neural networks in the history of humanity. Kudos!
in 15:07 shouldn't the b matrix be like : [b0 b1 … bk]? instead of bn?
The video has a lot of unnecessary information. It would be nice if you can cut them off.
Brilliant animation
It is a good video series that gives a lot of background and a rough understanding, but it is not possible to program a neural network from this.
I read some of the articles in the description and wrote a simple net in Rust converting 4 bit binary numbers into decimal numbers displayed on a 7-segment display with my son. ( https://github.com/etok414/simple_nn )
To help me explaining the mathematical details to my son (and as an exercise in Latex) I wrote a 6 page note about backpropagation.
The note treats the simplest possible network (2 input, 2 neurons and 2 outputs) in painstaiking detail.
Hope it'll help someone:
https://github.com/etok414/simple_nn/blob/master/latex/Back_propagation.pdf
Wow!
I ain't gonna lie, you, kind sir, are doing an awesome job! 🙂 Thank you!!!!
well i found this lecture lot better than that of Andrew NG… much clearer and easier to understand.
Hey Mr. Grant , I am a great fan of yours….I've always found your
videos so informative and clear..I want to connect with you whether you
are on Facebook or whats app…..Please e-mail me if you are seeing this
comment….
email id- suraj2895@gmail.com
Hey Mr. Grant , I am a great fan of yours….I've always found your
videos so informative and clear..I want to connect with you whether you
are on Facebook or whats app…..Please e-mail me if you are seeing this
comment….
email id- suraj2895@gmail.com
Hey Mr. Grant , I am a great fan of yours….I've always found your
videos so informative and clear..I want to connect with you whether you
are on Facebook or whats app…..Please e-mail me if you are seeing this
comment….
email id- suraj2895@gmail.com
Hey Mr. Grant , I am a great fan of yours….I've always found your
videos so informative and clear..I want to connect with you whether you
are on Facebook or whats app…..Please e-mail me if you are seeing this
comment….
email id- suraj2895@gmail.com
Great video. Very good visualization
Thank you very much for explaining such a complex topic.
15:00 should the bias vector not be of length k? (k x n)(n x 1) = (k x 1) vector
7549115417p
Welp i successfully created the most complicated random number generator i've ever seen.
Question: 14:49: should vector [b0,…,bn] (n-dimensional) not be [b0,….,bk] (k-dimensional)?
You are the best: you taught unteachable stuff in 19 minutes
hi! what happened to this teasered video series on probabilities? 😉
So what you’re telling me is that those “Are You A Robot?” captchas are useless now
Me: Can't read my own handwritten numbers
Neural network: I'll help you out
Très beau travail malgres que je ne peux prétendre connaître le sujet j'ai aimé votre façon d'expliquer, mais laissez moi vous dire que tous ces programmes sont dangereux pour l'avenir. C'est utile mais ce n'est pas celà là vrai vie , là on tourne vers le chaos dans un futur proche avec l'IA qui es amélioré sans cesse.
PS: Regarder le film Enigma c'est un bon film. D'ailleurs comme on peut le voir dans ce film les algorithmes servait à nous défendre à prévoir maintenant il vont servir à contrôler le monde pour avoir le pouvoir ultime comme "Dieu" l'oeil et les oreilles partout et presque même au delà car tous ces calculs servent même à anticiper. J'avais besoin d'écrire tout cela
10:15
Man, you are the best teacher I have ever come across.
thank you for the tutorials
Q = Quantum Mechanics
Q = Quinn Michaels
Q = Quantum
Machine learning = Rahula Club Follow instructions. If you want truth it's out there.<– (Added)
#tyler
#sirisys
#alice
#brainknuckles
#maytheswartzbewithyou
? Do you also have a version of this video without the pointless piano noise? It's absolutely useless.
? Thumbs down from me from the super annoying background piano while you are talking. Unfortunately, you are not the only one. There are videos about physics which also use this stupid background elevator-style music when someone is talking. WTF. Whoever artist thinks this is necessary, curse you for ruining an otherwise great video.
Thanks for simplifying this 🙂
so i’m colorblind, (duetranopia, occurs in around 10% of white males) so the green and red colors weren’t really distinguishable for me around the ~10 minute mark. just something to think about in the future when making videos that need color
This is an amazing explanation that helped me a lot… Thanks from a german engineer!!!
14：42 there is a mistake.bn—>bk
10:50부터 한국어 자막이 안나와요빨리 고쳐주세요
3:35 take 10 seconds to appreciate how awesome this animation is
I am a musician and artist. I am GED 6 months of technical college experience. I want to tell you I'm starting to grasp this little by little. I want to learn this. I have been catapulted into this yearning /craving for learning about machine learning via meditation and some. B+ Psilocybin Cubensis experiences. With that said, thank you for sharing your talents and work. I will continue to watch these over and over. Why? I think b/c I'm a creative person and this is creativity. Do we grasp the importance of creativity? In all it's malleable mediums. An individual or group passionate creative process then transcends time and space to connect with the recipient becomming part of their life. Our lives! Traveling some unseen conduit. Landing in our lap's like heart ache and hand grenade's. Art, music and ALL forms of creativity outdate religion, language and government. It's universally personal and the sinew that binds humanity. #ThIsIsNoTThEaLgOrItHiM on YT the Wellrose Hummingbird playlist for my music and slippery.sliding.slope on IG for art. Which I've been using images of neurological images, sound wave images etc to layer my art. Here's a song
Everything is Aligned https://youtu.be/Ftiw0rUq4es
And a song I wrote about nature and forgiveness
https://youtu.be/oWFk98pY-e8
?️??⤵️?️. ?️ ⤴️?️?
✨. ✨
✨. ✨
✨?️?⤴️
I remember watching this awhile ago, and after watching this again after watching VSauce's video on this on Minefield, (It's free now btw) this makes a lot of sense now and makes it seem a lot nicer.
I was mindblown when my prof in the lecture showed us that thereis only a 0.34% (or so it was a very low number) error rate for recognizing these handwritten numbers. Because so many numbers look similar in messy handwriting even I have problems to distinguish a messy 1 from a messy 7 or o
14:46 it should be b0-bk vector