3Blue1Brown
16 HN recommenders · recommended in 17 months, 2017–2025
18:40 · 25M views · Oct 5, 2017
3Blue1Brown's first chapter on deep learning explains what neurons and layers are and the math underlying a basic neural network, using handwritten digit recognition with visual animations.
HN treats it as the standard first stop for learning neural networks, praised for making the math intuitive.
19 comments from Hacker News
I'm in the same boat. For long time, I was interested in AI but at the same time intimidated by math. I'm relatively comfortable with discrete mathematics and classical algorithms and at the same time calculus and linear algebra is completely foreign to me. Also, I do not accept way to learn ML without good understanding of core principles behind it. So math is a must. A few months ago, I stumbled upon very amazing YouTube Channel 3Blue1Brown which explains math in very accessible way and at the same time I got feeling that I finally started understanding core ideas behind linear algebra and calculus. Just recently he published 4 videos about deep neural networks: this video [LINK] [LINK] [LINK] So my fear of ML was gone away and I'm very excited to explore whole new world for neural networks and other things like support vector machines etc
Essentially a computer neural network is just a lot of addition (and matrix multiplication) of floating point numbers. The parameters are the "strength" or "weights" of the connections between neurons on different layers and the "bias" of each neuron. If neuron Alice is connected to neuron Bob and Alice has a value of 0.7, and the weight of Alice's connection to bob is 0.5, then the value sent from Alice to Bob is 0.35. This value (and the values from all the other incoming connections) are summed at added to the neuron's negative bias. I highly recommend checking out 3blue1brown series on how neural nets, gradient descent, and the dot product (implemented as a matrix multiplication) all tie together: this video
For me 3brown1blue series: this video was an excellent introduction that made Andrej's videos understandable. Then I did 3 first chapters of fastai book, but found it too high level, while I was interested in how things works under the hood. Going through Andrej's makemore tutorials required quite a lot of time but it's definitely worth it. I used free tier of Google Colab until the last one. Pausing the video a lot after he explains what he plans to do and trying to do it by myself was a very rewarding way to learn, with a lot of "aha" moments.
this video 3Blue1Brown’s playlist on neural networks. Like other 3Blue1Brown videos, the visualisations and explanations of the math/concepts are so amazing, they give you the intuition behind the neural networks naturally.
3blue1brown videos are probably the best equivalent. Maybe a little basic? But really, all his math videos are just ridiculously good quality. this video