{"id":15480,"date":"2024-08-23T12:10:05","date_gmt":"2024-08-23T09:10:05","guid":{"rendered":"https:\/\/rss.eground-zerkalo.com\/?p=15480"},"modified":"2024-08-23T12:10:05","modified_gmt":"2024-08-23T09:10:05","slug":"super-study-guide-transformers-large-language-models-afshine-amidi-shervine-amidi","status":"publish","type":"post","link":"https:\/\/rss.eground-zerkalo.com\/?p=15480","title":{"rendered":"Super Study Guide: Transformers &#038; Large Language Models [Afshine Amidi, Shervine Amidi]"},"content":{"rendered":"<h2 class=\"\">\u0421\u043a\u043b\u0430\u0434\u0447\u0438\u043d\u0430: Super Study Guide: Transformers &amp; Large Language Models [Afshine Amidi, Shervine Amidi]<\/h2>\n<p> \t\t\t\t\t\u044f\u0437\u044b\u043a &#8212; \u0430\u043d\u0433\u043b\u0438\u0439\u0441\u043a\u0438\u0439<\/p>\n<p>  \t \t<img decoding=\"async\" src=\"https:\/\/v18.skladchik.org\/attachments\/2024-08-23_155028-jpg.1039656\/\" class=\"bbCodeImage LbImage\" alt=\"2024-08-23_155028.jpg\" \/> \t\t <\/p>\n<p> \u042d\u0442\u0430 \u043a\u043d\u0438\u0433\u0430 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 \u0441\u043e\u0431\u043e\u0439 \u043a\u0440\u0430\u0442\u043a\u043e\u0435 \u0438 \u0438\u043b\u043b\u044e\u0441\u0442\u0440\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0435 \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u043e \u0434\u043b\u044f \u0442\u0435\u0445, \u043a\u0442\u043e \u0445\u043e\u0447\u0435\u0442 \u043f\u043e\u043d\u044f\u0442\u044c \u0432\u043d\u0443\u0442\u0440\u0435\u043d\u043d\u044e\u044e \u0440\u0430\u0431\u043e\u0442\u0443 \u0431\u043e\u043b\u044c\u0448\u0438\u0445 \u044f\u0437\u044b\u043a\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0432 \u043a\u043e\u043d\u0442\u0435\u043a\u0441\u0442\u0435 \u0438\u043d\u0442\u0435\u0440\u0432\u044c\u044e, \u043f\u0440\u043e\u0435\u043a\u0442\u043e\u0432 \u0438\u043b\u0438 \u0434\u043b\u044f \u0443\u0434\u043e\u0432\u043b\u0435\u0442\u0432\u043e\u0440\u0435\u043d\u0438\u044f \u0441\u043e\u0431\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0433\u043e \u043b\u044e\u0431\u043e\u043f\u044b\u0442\u0441\u0442\u0432\u0430.<\/p>\n<p> <b>\u041e\u043d\u0430 \u0440\u0430\u0437\u0434\u0435\u043b\u0435\u043d \u043d\u0430 5 \u0447\u0430\u0441\u0442\u0435\u0439:<\/b><br \/> \u041e\u0441\u043d\u043e\u0432\u044b : \u0432\u0432\u0435\u0434\u0435\u043d\u0438\u0435 \u0432 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0435 \u0441\u0435\u0442\u0438 \u0438 \u0432\u0430\u0436\u043d\u044b\u0435 \u043a\u043e\u043d\u0446\u0435\u043f\u0446\u0438\u0438 \u0433\u043b\u0443\u0431\u043e\u043a\u043e\u0433\u043e \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0434\u043b\u044f \u043e\u0431\u0443\u0447\u0435\u043d\u0438\u044f \u0438 \u043e\u0446\u0435\u043d\u043a\u0438<br \/> \u0412\u0441\u0442\u0440\u0430\u0438\u0432\u0430\u043d\u0438\u0435 : \u0430\u043b\u0433\u043e\u0440\u0438\u0442\u043c\u044b \u0442\u043e\u043a\u0435\u043d\u0438\u0437\u0430\u0446\u0438\u0438, \u0432\u0441\u0442\u0440\u0430\u0438\u0432\u0430\u043d\u0438\u0435 \u0441\u043b\u043e\u0432 (word2vec) \u0438 \u0432\u0441\u0442\u0440\u0430\u0438\u0432\u0430\u043d\u0438\u0435 \u043f\u0440\u0435\u0434\u043b\u043e\u0436\u0435\u043d\u0438\u0439 (RNN, LSTM, GRU)<br \/> \u0422\u0440\u0430\u043d\u0441\u0444\u043e\u0440\u043c\u0435\u0440\u044b : \u043c\u043e\u0442\u0438\u0432\u0430\u0446\u0438\u044f \u043c\u0435\u0445\u0430\u043d\u0438\u0437\u043c\u0430 \u0441\u0430\u043c\u043e\u0432\u043e\u0441\u043f\u0440\u0438\u044f\u0442\u0438\u044f, \u043f\u043e\u0434\u0440\u043e\u0431\u043d\u044b\u0439 \u043e\u0431\u0437\u043e\u0440 \u0430\u0440\u0445\u0438\u0442\u0435\u043a\u0442\u0443\u0440\u044b \u043a\u043e\u0434\u0435\u0440\u0430-\u0434\u0435\u043a\u043e\u0434\u0435\u0440\u0430 \u0438 \u0441\u0432\u044f\u0437\u0430\u043d\u043d\u044b\u0445 \u0441 \u043d\u0435\u0439 \u0432\u0430\u0440\u0438\u0430\u0446\u0438\u0439, \u0442\u0430\u043a\u0438\u0445 \u043a\u0430\u043a BERT, GPT \u0438 T5, \u0430 \u0442\u0430\u043a\u0436\u0435 \u0441\u043e\u0432\u0435\u0442\u044b \u0438 \u0440\u0435\u043a\u043e\u043c\u0435\u043d\u0434\u0430\u0446\u0438\u0438 \u043f\u043e \u0443\u0441\u043a\u043e\u0440\u0435\u043d\u0438\u044e \u0432\u044b\u0447\u0438\u0441\u043b\u0435\u043d\u0438\u0439.<br \/> \u0411\u043e\u043b\u044c\u0448\u0438\u0435 \u044f\u0437\u044b\u043a\u043e\u0432\u044b\u0435 \u043c\u043e\u0434\u0435\u043b\u0438 : \u043e\u0441\u043d\u043e\u0432\u043d\u044b\u0435 \u043c\u0435\u0442\u043e\u0434\u044b \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0438 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u043d\u0430 \u043e\u0441\u043d\u043e\u0432\u0435 Transformer, \u0442\u0430\u043a\u0438\u0435 \u043a\u0430\u043a \u0431\u044b\u0441\u0442\u0440\u043e\u0435 \u043f\u0440\u043e\u0435\u043a\u0442\u0438\u0440\u043e\u0432\u0430\u043d\u0438\u0435, (\u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u0438\u0447\u0435\u0441\u043a\u0438 \u044d\u0444\u0444\u0435\u043a\u0442\u0438\u0432\u043d\u0430\u044f) \u0442\u043e\u043d\u043a\u0430\u044f \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0430 \u0438 \u043d\u0430\u0441\u0442\u0440\u043e\u0439\u043a\u0430 \u043f\u0440\u0435\u0434\u043f\u043e\u0447\u0442\u0435\u043d\u0438\u0439<br \/> \u041f\u0440\u0438\u043b\u043e\u0436\u0435\u043d\u0438\u044f : \u043d\u0430\u0438\u0431\u043e\u043b\u0435\u0435 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u0435\u043d\u043d\u044b\u0435 \u043f\u0440\u043e\u0431\u043b\u0435\u043c\u044b, \u0432\u043a\u043b\u044e\u0447\u0430\u044f \u0438\u0437\u0432\u043b\u0435\u0447\u0435\u043d\u0438\u0435 \u043d\u0430\u0441\u0442\u0440\u043e\u0435\u043d\u0438\u0439, \u043c\u0430\u0448\u0438\u043d\u043d\u044b\u0439 \u043f\u0435\u0440\u0435\u0432\u043e\u0434, \u0433\u0435\u043d\u0435\u0440\u0430\u0446\u0438\u044e \u0434\u043e\u043f\u043e\u043b\u043d\u0435\u043d\u043d\u043e\u0439 \u043f\u043e\u0438\u0441\u043a\u043e\u0432\u043e\u0439 \u0438\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0438\u0438 \u0438 \u043c\u043d\u043e\u0433\u043e\u0435 \u0434\u0440\u0443\u0433\u043e\u0435.<\/p>\n<p>     \t\u0421\u043f\u043e\u0439\u043b\u0435\u0440: \u041e\u0440\u0438\u0433\u0438\u043d\u0430\u043b \u043e\u043f\u0438\u0441\u0430\u043d\u0438\u044f: \tThis book is a concise and illustrated guide for anyone who wants to understand the inner workings of large language models in the context of interviews, projects or to satisfy their own curiosity.<\/p>\n<p> It is divided into 5 parts:<\/p>\n<p> Foundations: primer on neural networks and important deep learning concepts for training and evaluation<br \/> Embeddings: tokenization algorithms, word-embeddings (word2vec) and sentence embeddings (RNN, LSTM, GRU)<br \/> Transformers: motivation behind its self-attention mechanism, detailed overview on the encoder-decoder architecture and related variations such as BERT, GPT and T5, along with tips and tricks on how to speed up computations<br \/> Large language models: main techniques to tune Transformer-based models, such as prompt engineering, (parameter efficient) finetuning and preference tuning<br \/> Applications: most common problems including sentiment extraction, machine translation, retrieval-augmented generation and many more <\/p>\n<p> \u041c\u044f\u0433\u043a\u0430\u044f \u043e\u0431\u043b\u043e\u0436\u043a\u0430<br \/> \u0421\u043a\u0430\u043d, pdf<\/p>\n<p> \u0426\u0435\u043d\u0430: 37,99$ ~3500 \u0440\u0443\u0431 + \u0434\u043e\u0441\u0442\u0430\u0432\u043a\u0430<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0421\u043a\u043b\u0430\u0434\u0447\u0438\u043d\u0430: Super Study Guide: Transformers &amp; Large Language Models [Afshine Amidi, Shervine Amidi] \u044f\u0437\u044b\u043a &#8212; \u0430\u043d\u0433\u043b\u0438\u0439\u0441\u043a\u0438\u0439 \u042d\u0442\u0430 \u043a\u043d\u0438\u0433\u0430 \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u043b\u044f\u0435\u0442 \u0441\u043e\u0431\u043e\u0439 \u043a\u0440\u0430\u0442\u043a\u043e\u0435 \u0438 \u0438\u043b\u043b\u044e\u0441\u0442\u0440\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u043e\u0435 \u0440\u0443\u043a\u043e\u0432\u043e\u0434\u0441\u0442\u0432\u043e \u0434\u043b\u044f \u0442\u0435\u0445, \u043a\u0442\u043e \u0445\u043e\u0447\u0435\u0442 \u043f\u043e\u043d\u044f\u0442\u044c \u0432\u043d\u0443\u0442\u0440\u0435\u043d\u043d\u044e\u044e \u0440\u0430\u0431\u043e\u0442\u0443 \u0431\u043e\u043b\u044c\u0448\u0438\u0445 \u044f\u0437\u044b\u043a\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 \u0432 \u043a\u043e\u043d\u0442\u0435\u043a\u0441\u0442\u0435 \u0438\u043d\u0442\u0435\u0440\u0432\u044c\u044e, \u043f\u0440\u043e\u0435\u043a\u0442\u043e\u0432 \u0438\u043b\u0438 \u0434\u043b\u044f \u0443\u0434\u043e\u0432\u043b\u0435\u0442\u0432\u043e\u0440\u0435\u043d\u0438\u044f \u0441\u043e\u0431\u0441\u0442\u0432\u0435\u043d\u043d\u043e\u0433\u043e \u043b\u044e\u0431\u043e\u043f\u044b\u0442\u0441\u0442\u0432\u0430. \u041e\u043d\u0430 \u0440\u0430\u0437\u0434\u0435\u043b\u0435\u043d \u043d\u0430 5 \u0447\u0430\u0441\u0442\u0435\u0439: \u041e\u0441\u043d\u043e\u0432\u044b : \u0432\u0432\u0435\u0434\u0435\u043d\u0438\u0435 \u0432 \u043d\u0435\u0439\u0440\u043e\u043d\u043d\u044b\u0435 \u0441\u0435\u0442\u0438 \u0438 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-15480","post","type-post","status-publish","format-standard","hentry","category-rss"],"_links":{"self":[{"href":"https:\/\/rss.eground-zerkalo.com\/index.php?rest_route=\/wp\/v2\/posts\/15480","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/rss.eground-zerkalo.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/rss.eground-zerkalo.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/rss.eground-zerkalo.com\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/rss.eground-zerkalo.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=15480"}],"version-history":[{"count":0,"href":"https:\/\/rss.eground-zerkalo.com\/index.php?rest_route=\/wp\/v2\/posts\/15480\/revisions"}],"wp:attachment":[{"href":"https:\/\/rss.eground-zerkalo.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=15480"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/rss.eground-zerkalo.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=15480"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/rss.eground-zerkalo.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=15480"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}