{"product_id":"9783032254597","title":"Introduction to Deep Learning Neural Networks, Large Language Models and Agentic AI","description":"\u003ch3\u003eUndergraduate Topics in Computer Science\u003c\/h3\u003e\u003ch1\u003eIntroduction to Deep Learning\u003c\/h1\u003e\u003ch2\u003eNeural Networks, Large Language Models and Agentic AI\u003c\/h2\u003e\u003ch3\u003eSandro Skansi | Kristina Šekrst\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eComputers \/ Artificial Intelligence \/ General\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp class=\"MsoNormal\"\u003eThis textbook introduces deep learning in a style that is accessible, rigorous, and grounded in working code. It walks through the most widely used algorithms and architectures step by step, with mathematical derivations kept intuitive and Python examples woven through every chapter. \u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003eThe \u003cstrong\u003esecond edition\u003c\/strong\u003e keeps everything from the first, including convolutional networks, LSTMs, Word2vec, RBMs, DBNs, neural Turing machines, memory networks, and autoencoders. It then covers the systems that have reshaped the field since: generative adversarial networks, the transformer architecture and its attention mechanism, the full training pipeline behind modern large language models (LLMs), prompt engineering with real-life guardrail scenarios, parameter-efficient fine-tuning with LoRA, retrieval-augmented generation with vector databases, knowledge graphs, and agentic AI systems illustrated through an industrial case study.\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003eTopics and features:\u003c\/strong\u003e\u003c\/p\u003e\r\n\u003cul style=\"margin-top: 0cm;\" type=\"disc\"\u003e\r\n\u003cli class=\"MsoNormal\" style=\"mso-list: l0 level1 lfo1; tab-stops: list 36.0pt;\"\u003eIntroduces fundamentals of machine learning and mathematical and computational prerequisites for deep learning\u003c\/li\u003e\r\n\u003cli class=\"MsoNormal\" style=\"mso-list: l0 level1 lfo1; tab-stops: list 36.0pt;\"\u003eDiscusses feed-forward neural networks, convolutional networks, and recurrent architectures, and explores the modifications applicable to any neural network\u003c\/li\u003e\r\n\u003cli class=\"MsoNormal\" style=\"mso-list: l0 level1 lfo1; tab-stops: list 36.0pt;\"\u003eCovers the transformer architecture from first principles, including self-attention, multi-head attention, positional encoding, and a minimal annotated implementation\u003c\/li\u003e\r\n\u003cli class=\"MsoNormal\" style=\"mso-list: l0 level1 lfo1; tab-stops: list 36.0pt;\"\u003eReviews open research problems, from hallucinations and quadratic scaling to alignment faking and the interpretability of model internals\u003c\/li\u003e\r\n\u003c\/ul\u003e\r\n\u003cp class=\"MsoNormal\"\u003eThis proven, \u003cem\u003efully\u003c\/em\u003e \u003cem\u003erevised\u003c\/em\u003e textbook is written for graduate and advanced undergraduate students of computer science, cognitive science, and mathematics.\u003cspan style=\"mso-spacerun: yes;\"\u003e  \u003c\/span\u003eIt should prove equally valuable for readers in linguistics, logic, philosophy, and psychology.\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\"\u003e\u003cstrong\u003eSandro Skansi \u003c\/strong\u003eis an Associate Professor at the University of Zagreb, Croatia, where he teaches logic, political philosophy, artificial intelligence, and cognitive science. \u003cstrong\u003eKristina Šekrst\u003c\/strong\u003e is a research associate at the University of Zagreb and a principal engineer at Preamble AI.\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\n\u003cp class=\"MsoNormal\" style=\"mso-margin-top-alt: auto; mso-margin-bottom-alt: auto;\"\u003e\u003cstrong\u003eSandro Skansi \u003c\/strong\u003eis an Associate Professor at the University of Zagreb, Croatia, where he teaches logic, political philosophy, artificial intelligence, and cognitive science.\u003c\/p\u003e\r\n\u003cp class=\"MsoNormal\" style=\"mso-margin-top-alt: auto; mso-margin-bottom-alt: auto;\"\u003e\u003cstrong\u003eKristina Šekrst\u003c\/strong\u003e is a research associate at the University of Zagreb and a principal engineer at Preamble AI.\u003c\/p\u003e\n\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e08 August 2026\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eSpringer Nature Switzerland\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eSpringer\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9783032254597\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003ePaperback \/ softback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e104\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Springer Nature Switzerland","offers":[{"title":"Default Title","offer_id":47725804224652,"sku":"9783032254597","price":49.49,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783032254597.jpg?v=1780593367","url":"https:\/\/fh90cf-fv.myshopify.com\/products\/9783032254597","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}