[{"data":1,"prerenderedAt":87},["ShallowReactive",2],{"subject:deep-learning":3,"course-wordcounts":30,"nav:deep-learning":86},{"id":4,"title":5,"blurb":6,"body":7,"description":14,"extension":15,"meta":16,"module":11,"navigation":17,"path":18,"practice":19,"rawbody":20,"readingTime":21,"seo":24,"sources":25,"status":26,"stem":27,"summary":11,"topics":28,"__hash__":29},"course\u002F06.deep-learning\u002Findex.md","Deep Learning","Neural networks, gradient descent, and how machines learn patterns too subtle to program by hand.",{"type":8,"value":9,"toc":10},"minimark",[],{"title":11,"searchDepth":12,"depth":12,"links":13},"",2,[],"Neurons and layers, backpropagation and gradient descent, convolutional and recurrent networks, attention and transformers, regularization, and the training tricks that make it all work. Notes for this subject are coming soon.","md",{},true,"\u002Fdeep-learning",[],"---\ntitle: Deep Learning\nstatus: placeholder\nblurb: >-\n  Neural networks, gradient descent, and how machines learn patterns too subtle\n  to program by hand.\ndescription: >-\n  Neurons and layers, backpropagation and gradient descent, convolutional and\n  recurrent networks, attention and transformers, regularization, and the\n  training tricks that make it all work. 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