{"id":9830,"date":"2026-08-10T10:11:51","date_gmt":"2026-08-10T10:11:51","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/oreilly-how-llms-understand-generate-human-language-2024-9\/"},"modified":"2026-08-10T10:11:51","modified_gmt":"2026-08-10T10:11:51","slug":"oreilly-how-llms-understand-generate-human-language-2024-9","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/oreilly-how-llms-understand-generate-human-language-2024-9\/","title":{"rendered":"Oreilly \u2013 How LLMs Understand &#038; Generate Human Language 2024-9"},"content":{"rendered":"<div class=\"w-post-elm post_content\">\n<h2><span style=\"vertical-align: inherit\">Description<\/span><\/h2>\n<p><span style=\"vertical-align: inherit\">How LLMs Understand &amp; Generate Human Language. Generative language models, such as ChatGPT and Microsoft Bing, have become everyday tools for many of us, but the inner workings of these models remain a mystery to many others. How does ChatGPT know what the next word should be? How does it understand the meaning of the text you provide it? Everyone, from those who have never interacted with a chatbot to those who use it regularly, can benefit from a basic understanding of how these language models work. This course answers some of your basic questions about how generative AI works.<\/span><\/p>\n<p data-sourcepos=\"11:1-11:730\"><span style=\"vertical-align: inherit\">In this course, participants will be introduced to the concept of \u201cword embeddings\u201d: not only how they are used in these models, but also how they can be used to analyze large amounts of textual information using concepts such as vector storage and augmented retrieval generation. Understanding how these models work is important because it helps you understand both their capabilities and their limitations. This knowledge will allow you to critically examine the results of these models and gain a better understanding of their strengths and weaknesses. Furthermore, understanding the fundamentals of how LLMs work can help you better understand future developments in this field and how to more effectively interact with this emerging technology.<\/span><\/p>\n<h3 data-sourcepos=\"13:1-13:24\"><strong><span style=\"vertical-align: inherit\">What you will learn<\/span><\/strong><\/h3>\n<ul data-sourcepos=\"15:1-21:0\">\n<li data-sourcepos=\"15:1-15:59\"><span style=\"vertical-align: inherit\">How to convert human language into mathematics that models understand.<\/span><\/li>\n<li data-sourcepos=\"16:1-16:55\"><span style=\"vertical-align: inherit\">How output words are selected by generative language models.<\/span><\/li>\n<li data-sourcepos=\"17:1-17:77\"><span style=\"vertical-align: inherit\">Why some application strategies and specific tasks perform better with LLMs than others.<\/span><\/li>\n<li data-sourcepos=\"18:1-18:71\"><span style=\"vertical-align: inherit\">The concept of \u201cword embedding\u201d and how it can be used to empower LLMs.<\/span><\/li>\n<li data-sourcepos=\"19:1-19:64\"><span style=\"vertical-align: inherit\">The concept of \u201cvector storage\/retrievable augmented production\u201d and its importance.<\/span><\/li>\n<li data-sourcepos=\"20:1-21:0\"><span style=\"vertical-align: inherit\">How to critically evaluate the results obtained from large language models.<\/span><\/li>\n<\/ul>\n<h3 data-sourcepos=\"22:1-22:30\"><strong><span style=\"vertical-align: inherit\">This course is suitable for people who:<\/span><\/strong><\/h3>\n<ul data-sourcepos=\"24:1-27:120\">\n<li data-sourcepos=\"24:1-24:64\"><span style=\"vertical-align: inherit\">They are interested in deciphering the performance of generative language models.<\/span><\/li>\n<li data-sourcepos=\"25:1-25:83\"><span style=\"vertical-align: inherit\">They want to be able to talk about these models with their colleagues in an informed way.<\/span><\/li>\n<li data-sourcepos=\"26:1-26:107\"><span style=\"vertical-align: inherit\">They want to explore some of the black box ambiguities of LLMs but don\u2019t have enough time for deep, hands-on learning.<\/span><\/li>\n<li data-sourcepos=\"27:1-27:120\"><span style=\"vertical-align: inherit\">In their work, they have potential applications for ChatGPT or other text-based generative AI or embeddable storage methods.<\/span><\/li>\n<\/ul>\n<h3><span style=\"vertical-align: inherit\">Course Details How LLMs Understand &amp; Generate Human Language<\/span><\/h3>\n<ul>\n<li><span style=\"vertical-align: inherit\">Publisher: <\/span><a href=\"https:\/\/href.li\/?https:\/\/www.oreilly.com\/library\/view\/how-llms-understand\/9780135414309\/\" target=\"_blank\" rel=\"noopener\"><span style=\"vertical-align: inherit\">Oreilly<\/span><\/a><\/li>\n<li><span style=\"vertical-align: inherit\">Instructor: <\/span><a href=\"https:\/\/downloadlynet.ir\/tag\/kate-harwood\/\"><span style=\"vertical-align: inherit\">Kate Harwood<\/span><\/a><\/li>\n<li><span style=\"vertical-align: inherit\">Training level: Beginner to advanced<\/span><\/li>\n<li><span style=\"vertical-align: inherit\">Training duration: 1 hour and 54 minutes<\/span><\/li>\n<\/ul>\n<h3><span style=\"vertical-align: inherit\">Course headings<\/span><\/h3>\n<div class=\"ud-block-list-item ud-block-list-item-small ud-block-list-item-tight ud-block-list-item-neutral ud-text-sm\">\n<ol>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Introduction<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">How LLMs Understand Generate Human Language: Introduction<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Lesson 1: Introduction to LLMs and Generative AI<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Learning objectives<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">1.1 LLMs<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">1.2 Generative AI<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">1.3 Machine Learning General Overview<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Lesson 2: Word Embeddings<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Learning objectives<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">2.1 How Do AI Models \u201cRead\u201d Input?<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">2.2 How Do We Capture Word Meanings?<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">2.3 Word Embedding Space<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">2.4 How Do LLMs Learn Word Embeddings?<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">2.5 Tokenization<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">2.6 Putting It All Together<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">2.7 A Cool Side-Effect<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Lesson 3: Word Embeddings in Generative Language Models<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Learning objectives<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">3.1 How Are Word Embeddings Used in Generative Language Models?<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">3.2 RNNs<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">3.3 Transformers: Attention<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">3.4 Transformers: Contextual Word Embeddings<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">3.5 Transformers for Generation<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">3.6 What Works Well (and What Can Go Wrong) When We Train Models on Word Embeddings?<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Lesson 4: Other Use Cases for Embeddings<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Learning objectives<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">4.1 Summary<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">4.2 Vector Storage<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">4.3 Retrieval Augmented Generation<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">Summary<\/span><\/li>\n<li dir=\"ltr\" style=\"text-align: left\"><span style=\"vertical-align: inherit\">How LLMs Understand Generate Human Language: Summary<\/span><\/li>\n<\/ol>\n<\/div>\n<h3><span style=\"vertical-align: inherit\">Course images<\/span><\/h3>\n<h2><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-978568 size-full\" src=\"https:\/\/downloadly.ir\/wp-content\/uploads\/2025\/04\/How-LLMs-Understand-Generate-Human-Language.png\" alt=\"How LLMs Understand &amp; Generate Human Language\" width=\"1137\" height=\"360\"><\/h2>\n<h3><span style=\"vertical-align: inherit\">Sample course video<\/span><\/h3>\n<div style=\"width: 640px;\" class=\"wp-video\"><span class=\"mejs-offscreen\">Video Player<\/span><\/p>\n<div id=\"mep_0\" class=\"mejs-container mejs-container-keyboard-inactive wp-video-shortcode mejs-video\" tabindex=\"0\" role=\"application\" aria-label=\"Video Player\" style=\"width: 640px; height: 360px; min-width: 217px;\">\n<div class=\"mejs-inner\">\n<div class=\"mejs-mediaelement\"><mediaelementwrapper id=\"video-161936-1\"><video class=\"wp-video-shortcode\" id=\"video-161936-1_html5\" width=\"640\" height=\"360\" preload=\"metadata\" src=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/How_LLMs_Understand_and_Generate_Human_Language_Downloadly.ir.mp4?_=1\" style=\"width: 640px; height: 360px;\"><source type=\"video\/mp4\" src=\"https:\/\/dl.downloadly.ir\/Files\/Elearning\/Sample\/How_LLMs_Understand_and_Generate_Human_Language_Downloadly.ir.mp4?_=1\"><a 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title=\"Fullscreen\" aria-label=\"Fullscreen\" tabindex=\"0\"><\/button><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div>\n<h3><span style=\"vertical-align: inherit\">Installation Guide<\/span><\/h3>\n<p><span style=\"vertical-align: inherit\">After Extract, view with your favorite player.<\/span><\/p>\n<p><span style=\"vertical-align: inherit\">Subtitles: None<\/span><\/p>\n<p><span style=\"vertical-align: inherit\">Quality: 720p<\/span><\/p>\n<\/div>\n<h3><span style=\"vertical-align: inherit\">Download link<\/span><\/h3>\n<p><a href=\"https:\/\/dl3.downloadly.ir\/Files\/Elearning\/Oreilly_How_LLMs_Understand_&amp;_Generate_Human_Language_2024-9_Downloadly.ir.rar?nocache=1786136263\"><span style=\"vertical-align: inherit\">Download file \u2013 369 MB<\/span><\/a><\/p>\n<p><span style=\"vertical-align: inherit\">File(s) password: www.downloadly.ir<\/span><\/p>\n<h3><span style=\"vertical-align: inherit\">File size<\/span><\/h3>\n<p><span style=\"vertical-align: inherit\">369 MB<\/span><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Description How LLMs Understand &amp; Generate Human Language. Generative language models, such as ChatGPT and Microsoft Bing, have become everyday tools for ma<\/p>\n","protected":false},"author":1,"template":"","dgi_category":[10458],"dgi_tag":[84151,84152,84153,84154,84155,84156],"class_list":["post-9830","digital_item","type-digital_item","status-publish","has-post-thumbnail","hentry","dgi_category-video-tutorials","dgi_tag-course-how-llms-understand-generate-human-language","dgi_tag-download-course-how-llms-understand-generate-human-language","dgi_tag-download-how-llms-understand-generate-human-language","dgi_tag-free-download-how-llms-understand-generate-human-language","dgi_tag-free-how-llms-understand-generate-human-language","dgi_tag-kate-harwood"],"_links":{"self":[{"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/digital_item\/9830","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/digital_item"}],"about":[{"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/types\/digital_item"}],"author":[{"embeddable":true,"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"version-history":[{"count":0,"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/digital_item\/9830\/revisions"}],"wp:attachment":[{"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/media?parent=9830"}],"wp:term":[{"taxonomy":"dgi_category","embeddable":true,"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/dgi_category?post=9830"},{"taxonomy":"dgi_tag","embeddable":true,"href":"https:\/\/nokobox.com\/index.php\/wp-json\/wp\/v2\/dgi_tag?post=9830"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}