Unilibrary. Oliy ta'lim muassasalarining yagona elektron kutubxona axborot tizimi.

Essentials of MIS fourteenth edition

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Tasviriy san'at o'qitish metodikasi

Ushbu darlik 60110500- "Tasviriy san'at va muhandislik grafikasi yo'nalishi bakalavriat bosqichi talabalari uchun mo'ljallangan bo'lib bugungi kun talabalarini hisobga olingan holda tuzildi

Large Vision-Language Models. Pre-training, Prompting, and Applications

The rapid progress in the field of large multimodal foundation models, especially vision-language models, has dramatically transformed the landscape of machine learning, computer vision, and natural language processing. These powerful models, trained on vast amounts of multimodal data mixed with images and text, have demonstrated remarkable capabilities in tasks ranging from image classification and object detection to visual content generation and question answering. This book provides a comprehensive and up-to-date exploration of large vision-language models, covering the key aspects of their pre-training, prompting techniques, and diverse real-world computer vision applications. It is an essential resource for researchers, practitioners, and students in the fields of computer vision, natural language processing, and artificial intelligence.

Large Vision-Language Models. Pre-training, Prompting, and Applications

The rapid progress in the field of large multimodal foundation models, especially vision-language models, has dramatically transformed the landscape of machine learning, computer vision, and natural language processing. These powerful models, trained on vast amounts of multimodal data mixed with images and text, have demonstrated remarkable capabilities in tasks ranging from image classification and object detection to visual content generation and question answering. This book provides a comprehensive and up-to-date exploration of large vision-language models, covering the key aspects of their pre-training, prompting techniques, and diverse real-world computer vision applications. It is an essential resource for researchers, practitioners, and students in the fields of computer vision, natural language processing, and artificial intelligence.

Информационные технологии в технических системах.

Программирование является ключевым инструментом в области информационных технологий, поскольку позволяет создавать программное обеспечение для управления информацией и процессами в компьютерных системах.

Qurilishda axborot texnologiyalari

Ushbu darslik axborot texnologiyalarini rivojlantirishning nazariy va amaliy jihatlariga va avtomatlashtirilgan dasturiy ta’minotda ma’lumotlarni qayta ishlashning texnologik jarayoniga bag‘ishlashgan.

Models Demystified. A Practical Guide from Linear Regression to Deep Learning

Unlock the Power of Data Science and Machine Learning. In this comprehensive guide, we delve into the world of data science, machine learning, and AI modeling, providing readers with a robust foundation and practical skills to tackle real-world problems. From basic modeling techniques to advanced machine learning algorithms, this book covers a wide range of topics, ensuring that readers at all levels can benefit from its content. Each chapter is meticulously crafted to offer clear explanations, hands-on examples, and code snippets in both Python and R, making complex concepts accessible and actionable. Additional focus is placed on model interpretation and estimation, common data issues, modeling pitfalls to avoid, and best practices for modeling in general.

методикаи корхои тарбиявй

Дастури омузншй тальми ибтидон омода карда шуда дар он масьалахон назариявй методалогия ва омилхои амални методологияи

Ilmiy tadqiqot metodologiyasi

Darslikda ilm -fanning metodologik asoslari bayon etilgan, ilmiy bilishning turli darajalari koʻrib chiqilgan. Ilmiy tatqiqot ishlarini oʻtkazishning bosqichlari hamda tatqiqot yoʻnalishini tanlash masalalari, hamda magistrlik dissertatsiyasining tayyorlashga qoʻyiladigan talablar keltirilgan.

Mathematical Foundations for Deep Learning

Mathematical Foundations for Deep Learning bridges the gap between theoretical mathematics and practical applications in artificial intelligence (AI). This guide delves into the fundamental mathematical concepts that power modern deep learning, equipping readers with the tools and knowledge needed to excel in the rapidly evolving field of artificial intelligence. Designed for learners at all levels, from beginners to experts, the book makes mathematical ideas accessible through clear explanations, real-world examples, and targeted exercises. Readers will master core concepts in linear algebra, calculus, and optimization techniques; understand the mechanics of deep learning models; and apply theory to practice using frameworks like TensorFlow and PyTorch. By integrating theory with practical application, Mathematical Foundations for Deep Learning prepares you to navigate the complexities of AI confidently. Whether you are aiming to develop practical skills for AI projects, advance to emerging trends in deep learning, or lay a strong foundation for future studies, this book serves as an indispensable resource for achieving proficiency in the field. Embark on an enlightening journey that fosters critical thinking and continuous learning. Invest in your future with a solid mathematical base, reinforced by case studies and applications that bring theory to life, and gain insights into the future of deep learning.

Высшая matemaтика для гуманитарных направлений

Кроме систематизированного элементарного изложения теоретического мате риала по каждой теме в качестве примеров решено большое число практических задач и упражнений разного уровня трудности. В конце каждой темы приводится список контрольных вопросов, ответы на которые позволяют учащемуся самостоятельно оценить уровень его теоретической подготовки к данному моменту обучения. Каждая тема завершается заданиями для аудиторной и домашней работы и вариантами индивидуальных домашних заданий.

Everyday Business english

The books in this series present and practise spoken English and practical writing for everyday communication; they feature key words and expressions which will help you in a wide range of work situations. The target language is introduced through short dialogues and texts, and developed in language notes and practice exercises.

A Beginner’s Guide to Generative AI. An Introductory Path to Diffusion Models, ChatGPT and LLMs

Generative AI has emerged as one of the groundbreaking technologies of the century. This book aims to assist readers in exploring this fascinating domain while equipping you with the necessary background information and recommendations. The book embarks on a long and profound journey, beginning by constructing a clear and strong pictures of the fundamental approaches and concepts that define generative AI. Readers will explore the architectures of some of the most commonly used models, such as Transformers, ChatGPT, and Google Gemini, and learn how these technologies have achieved such impressive results. This book is intended for novice readers, and the basics of working with generative AI do not require any prior training. From this perspective, we will proceed from the most basic concepts to more advanced topics in a sequential and accessible manner. Whether you are a student, a working professional, or simply someone curious about what AI can offers you will find this guide highly valuable.

Асосҳои алгебраи хаттй

Васоити таълими мазкур мувофики барномаи фанни алгебра ва назарияи ададҳо барои донишчўён ва омўзгорони факултетҳои математика ва донишгоҳҳо ва колечи омўзгорй,

FIZIKAVIY TADQIQOT USULLARI

Ushbu darslik molekulalarning elektron, infraqizil, yadro magnit rezonansi ('H va C) va mass-spektrlarini o'rganish bo'yicha amaliy mashg'ulotlar o'tkazishga mo'ljallangan. Darslikda tegishli spektrlarni talqin qilish bo'yicha bajariladigan amaliy ishlarning bayoni, bajarish bo'yicha ko'rsatmalar, maslahatlar, mustaqil ishlash bo'yicha masalalar va ba'zi zarur ma'lumotlar keltirilgan. Har bir mavzu bo'yicha bitta yoki ikkita amaliy ish bajarib ko'rsatilgan, mustaqil bajarish uchun berilgan. Darslikda mass-hamda bir va ikki o'lchamli YaMR spektrlarini talqin qilishga katta e'tibor berilgan. Darslik universitetlarning kimyo fakultetlari yuqori kurs talabalari va magistrlariga mo'ljallangan bo'lib undan, fizika va farmasevtika fakultetlarining talabalari, oliy o'quv yurtining o'qituvchilari, ilmiy tadqiqot institutlari hamda zavod-fabrika laboratoriyalarining xodimlari foydalanishi mumkin.

Texnalogiya ta'limi metodikasi

Mazkur darslik 60112300- texnologiya ta'lim yo'nalishi talabalari va umumiy o'rta ta'lim muassasalarining Texnalogiya fani o'qituvchilari uchun mo'ljallangan bo'lib unda fanning maqsad va vazifalari metodologik asoslari tarixiy taraqqiyoti didaktik asoslari