[{"data":1,"prerenderedAt":78},["ShallowReactive",2],{"term-n\u002Fnlp":3,"related-n\u002Fnlp":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":53,"sitemap":54,"stem":57,"subcategory":58,"__hash__":59},"terms\u002Fterms\u002Fn\u002Fnlp.md","NLP","Natural Language Processing",{"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",{},"NLP is the branch of AI that deals with human language — reading it, writing it, translating it, summarizing it. Before LLMs, NLP involved a lot of hand-crafted rules and painful feature engineering. Now you just prompt Claude. The whole field changed overnight. NLP is why chatbots stopped being terrible.",[11,20,22],{"id":21},"real-talk","Real Talk",[16,24,25],{},"Natural Language Processing is the subfield of AI concerned with enabling computers to understand, generate, and manipulate human language. Core NLP tasks include tokenization, part-of-speech tagging, named entity recognition, sentiment analysis, machine translation, and text generation. LLMs have superseded most classical NLP methods.",[11,27,29],{"id":28},"when-youll-hear-this","When You'll Hear This",[16,31,32],{},"\"We need NLP to extract entities from the customer emails.\" \u002F \"The LLM revolution basically ate classical NLP.\"",{"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","NLP is the branch of AI that deals with human language — reading it, writing it, translating it, summarizing it.","beginner","md","n",{},true,"\u002Fterms\u002Fn\u002Fnlp",[6,49,50,51,52],"LLM","Tokenizer","Embedding","Transformer",{"title":5,"description":41},{"changefreq":55,"priority":56},"weekly",0.7,"terms\u002Fn\u002Fnlp",null,"t72rONrVCJ4izj9rk8O_kekTHpQ1PNCaLal3HZolTgw",[61,65,69,72,75],{"title":51,"path":62,"acronym":58,"category":40,"difficulty":63,"description":64},"\u002Fterms\u002Fe\u002Fembedding","intermediate","An embedding is turning words, sentences, or entire documents into lists of numbers (vectors) that capture their meaning.",{"title":49,"path":66,"acronym":67,"category":40,"difficulty":42,"description":68},"\u002Fterms\u002Fl\u002Fllm","Large Language Model","An LLM is a humongous AI that read basically the entire internet and learned to predict what words come next, really really well.",{"title":6,"path":70,"acronym":5,"category":40,"difficulty":42,"description":71},"\u002Fterms\u002Fn\u002Fnatural-language-processing","The full name for NLP — making computers understand and produce human language.",{"title":50,"path":73,"acronym":58,"category":40,"difficulty":63,"description":74},"\u002Fterms\u002Ft\u002Ftokenizer","A tokenizer chops text into pieces that the AI model can understand — but not in ways humans would expect.",{"title":52,"path":76,"acronym":58,"category":40,"difficulty":63,"description":77},"\u002Fterms\u002Ft\u002Ftransformer","The Transformer is THE architecture behind all modern AI. ChatGPT, Claude, Midjourney, Whisper — all transformers under the hood. The key innovation?",1776518296861]