[{"data":1,"prerenderedAt":86},["ShallowReactive",2],{"video-intro-neural-networks":3},{"id":4,"title":5,"body":6,"date":72,"description":73,"extension":74,"meta":75,"navigation":76,"path":77,"seo":78,"stem":79,"tags":80,"youtubeId":84,"__hash__":85},"videos\u002Fvideos\u002Fintro-neural-networks.md","But What Is a Neural Network?",{"type":7,"value":8,"toc":65},"minimark",[9,14,23,27,43,47,50],[10,11,13],"h2",{"id":12},"about-this-video","About this Video",[15,16,17,18,22],"p",{},"This is the first video in 3Blue1Brown's ",[19,20,21],"em",{},"Deep Learning"," series. It builds an intuitive understanding of how neural networks learn without assuming any prior ML knowledge.",[10,24,26],{"id":25},"what-youll-learn","What You'll Learn",[28,29,30,34,37,40],"ul",{},[31,32,33],"li",{},"What neurons and layers are",[31,35,36],{},"How a network transforms input data through layers",[31,38,39],{},"The idea of learning as adjusting weights and biases",[31,41,42],{},"Why depth (multiple layers) matters",[10,44,46],{"id":45},"notes","Notes",[15,48,49],{},"Watch this before touching any ML framework. The visual intuition from this video makes gradient descent, backpropagation, and loss functions much easier to understand later.",[15,51,52,56,57,64],{},[53,54,55],"strong",{},"Next",": Watch the follow-up on ",[58,59,63],"a",{"href":60,"rel":61},"https:\u002F\u002Fwww.youtube.com\u002Fwatch?v=IHZwWFHWa-w",[62],"nofollow","gradient descent",".",{"title":66,"searchDepth":67,"depth":67,"links":68},"",2,[69,70,71],{"id":12,"depth":67,"text":13},{"id":25,"depth":67,"text":26},{"id":45,"depth":67,"text":46},"2026-03-25","3Blue1Brown's classic visual introduction to neural networks — the best starting point for anyone new to deep learning.","md",{},true,"\u002Fvideos\u002Fintro-neural-networks",{"title":5,"description":73},"videos\u002Fintro-neural-networks",[81,82,83],"neural-networks","beginners","3blue1brown","aircAruvnKk","lJsWJ2lWK0q3S0RJB26Z6aS5c18H3ytUqf2hdbFtLgs",1776276582891]