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

Group Dynamics for Teams

Many people helped shape this book. My understanding of work teams, including both manufacturing and professional teams, was fostered by the many opportunities I have had to study and consult with actual teams in industry.

Экономика замкнутого цикла и устойчивое управление отходами

Данный курс представляет собой междисциплинарное руководство по управлению отходами и экономике замкнутого цикла. Представленный материал поможет студентам понять движущие силы образования отходов, экологические, социальные и экономические последствия образования отхо дов, ознакомиться с технологиями управления отходами, разобраться в меха низмах внедрения экономики замкнутого цикла в сектор управления отхо дами, получить представление о воздействии сектора управления твердыми коммунальными отходами на климат. Особенностью курса является доступ ное для понимания изложение сложного материала.

Metrologiya va oʻlchashlar yagonaligini ta'minlash

Darslikda metrologiya fanining axamiyati va rivojlanishi, metrologiyaning rivojlanish bosqichlari, ishlab chiqarish va uning tarmoqlarini metrologik ta'minlash, respublikada metrologiyaning rivojlanishi, fizik-kimyoviy oʻlchovlarning xususiyatlari va boshqa m`lumotlar berilgan.

Thinking Programs. Logical Modeling and Reasoning About Languages, Data, Computations, and Executions. (2nd ed.)

This book describes some basic principles that allow developers of computer programs (computer scientists, software engineers, programmers) to clearly think about the artifacts they deal with in their daily work: data types, programming languages, programs written in these languages that compute wanted outputs from given inputs, and programs that describe continuously executing systems. The core message is that clear thinking about programs can be expressed in a single, universal language, the formal language of logic. Apart from its universal elegance and expressiveness, this “logical” approach to the formal modeling of, and reasoning about, computer programs has another advantage: due to advances in computational logic (automated theorem proving, satisfiability solving, model checking), nowadays much of this process can be supported by software. This book therefore accompanies its theoretical elaborations by practical demonstrations of various systems and tools that are based on or make use of the presented logical underpinnings.

Navoiyshunoslik

Ushbu darslik respublika oliy o'quv yurtlari o'zbek filologiyasi hamda o'zbek tili va adabiyotini o'qitish, shuningdek, nofilologik yo'nalishlarda tahsil olayotgan talabalar uchun mo'ljallangan bo'lib, unda Alisher Navoiy hayoti va ijodi hamda asarlan poetikasi bilan bog'liq eng muhim ma'lumotlar qamrab olingan, buyuk mutafakkir ijodiga doir yangicha talqinlar berilgan. Darslik navoiyshunoslikda qo'lga kiritilgan eng so'nggi yutuqlarni o'zida aks ettirganligi bilan alohida ahamiyat kasb etadi.

Favqulodda vaziyatlarda xavfsizlik.

Favqulodda vaziyatlarning oldini olish oldindan qabul qilingan va favqulodda vaziyatlar xavfini maksimal darajada kamaytirishga yo‘naltirilgan chora-tadbirlar kompleksidir

Essentials of MIS fourteenth edition

Microsoft and or its respective suppliers make no representations about the suitability of the information contained in the documents and related graphics published as part of the services for any purpose. All such documents and related graphics are provided “as is” without warranty of any kind. Microsoft and/or its respective suppliers hereby disclaim all warranties and conditions with regard to this information, including all warranties and conditions of merchantability, whether express, implied or statutory, fitness for a particular purpose, title and non-infringement.

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.