[{"data":1,"prerenderedAt":77},["ShallowReactive",2],{"term-t\u002Ftransfer-learning":3,"related-t\u002Ftransfer-learning":60},{"id":4,"title":5,"acronym":6,"body":7,"category":40,"description":41,"difficulty":42,"extension":43,"letter":44,"meta":45,"navigation":46,"path":47,"related":48,"seo":54,"sitemap":55,"stem":58,"subcategory":6,"__hash__":59},"terms\u002Fterms\u002Ft\u002Ftransfer-learning.md","Transfer Learning",null,{"type":8,"value":9,"toc":33},"minimark",[10,15,19,23,26,30],[11,12,14],"h2",{"id":13},"eli5-the-vibe-check","ELI5 — The Vibe Check",[16,17,18],"p",{},"Transfer Learning is using knowledge a model already has from one task to help it with a different task. A model that learned to understand images of dogs can transfer that knowledge to recognize cats much faster. It's like a chef who already knows French cuisine picking up Italian much faster than someone starting from zero.",[11,20,22],{"id":21},"real-talk","Real Talk",[16,24,25],{},"Transfer learning is a machine learning paradigm where a model trained on one task is adapted to a different but related task. The pre-trained model's learned representations are reused, typically through fine-tuning. It dramatically reduces data and compute requirements and is the basis for the modern 'pre-train then fine-tune' paradigm.",[11,27,29],{"id":28},"when-youll-hear-this","When You'll Hear This",[16,31,32],{},"\"Transfer learning lets us train on only 1000 examples.\" \u002F \"Fine-tuning is a form of transfer learning.\"",{"title":34,"searchDepth":35,"depth":35,"links":36},"",2,[37,38,39],{"id":13,"depth":35,"text":14},{"id":21,"depth":35,"text":22},{"id":28,"depth":35,"text":29},"ai","Transfer Learning is using knowledge a model already has from one task to help it with a different task.","intermediate","md","t",{},true,"\u002Fterms\u002Ft\u002Ftransfer-learning",[49,50,51,52,53],"Fine-tuning","Pre-training","Model","Weights","Deep Learning",{"title":5,"description":41},{"changefreq":56,"priority":57},"weekly",0.7,"terms\u002Ft\u002Ftransfer-learning","U1i6nP97zU-gzmwC3vf0JJcm2p3uJTb6pJpn0--98wY",[61,64,67,71,74],{"title":53,"path":62,"acronym":6,"category":40,"difficulty":42,"description":63},"\u002Fterms\u002Fd\u002Fdeep-learning","Deep Learning is Machine Learning that's been hitting the gym.",{"title":49,"path":65,"acronym":6,"category":40,"difficulty":42,"description":66},"\u002Fterms\u002Ff\u002Ffine-tuning","Fine-tuning is like taking a smart graduate student who knows everything and then sending them to a specialist bootcamp.",{"title":51,"path":68,"acronym":6,"category":40,"difficulty":69,"description":70},"\u002Fterms\u002Fm\u002Fmodel","beginner","A model is the trained AI — the finished product.",{"title":50,"path":72,"acronym":6,"category":40,"difficulty":42,"description":73},"\u002Fterms\u002Fp\u002Fpre-training","Pre-training is the first massive phase where an AI reads basically the entire internet and learns to predict the next word billions of times.",{"title":52,"path":75,"acronym":6,"category":40,"difficulty":42,"description":76},"\u002Fterms\u002Fw\u002Fweights","Weights are the numbers inside a neural network that determine what it knows and how it behaves — they're the AI's 'brain cells.",1776518319786]