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

Code: The Hidden Language of Computer Hardware and Software. Second Edition

The first edition of this book was published in September 1999. With much delight I realized that I had finally written a book that would never need revising! This was in stark contrast to my first book, which was about programming applications for Microsoft Windows. That one had already gone through five editions in just ten years. My second book on the OS/2 Presentation Manager (the what?) became obsolete much more quickly.

Парогенераторы

В книге приведены характеристики энергетических топлив, изложены теоретические основы их горения, описаны различные типы топок, приведены схемы и конструкции паровых котлов, парогенераторов АЭС, ПГУ и МГД-установок.

Beginner's Step-by-Step Coding Course

Coding skills are in high demand and the need for programmers is still growing. Covering three of the most popular languages for new coders, this book uses a graphic method to break complex subjects into user-friendly chunks, bringing essential skills within easy reach. Each chapter contains tutorials on practical projects designed to teach you the main applications of each language, such as building websites, creating games, and designing apps. The book also looks at many of the main coding languages that are out there, outlining the key applications of each language, so you can choose the right language for you.

Adabiyotshunoslikka kirish

Darslik respublikamizdagi universitetlar, pedagogika, madaniyat va san'at institutlari, kollejlar, litseylar talabalari, maktab o'qituvchilariga mo'ljallangan.

Цифровая экономика и индустрия 5.0

В учебном пособии «Цифровая экономика и Индустрия 5.0» представлены результаты исследований авторов, отражающие научно-методические положения концепций цифрового развития экономики и промышленности. Рассмотрены ключевые аспекты цифровой экономики, включая технологические, экономические и социальные факторы, которые играют важную роль в формировании Индустрии 5.0

Umumiy geologoya

Darslik kosmik, geofizik va boshqa izlanishlar natijasida olingan ma`lumotlarni e`tiborga olib tuzulgan.

ВВЕДЕНИЕ В СПЕЦИАЛИЗАЦИЮ ИЗБРАННОГО ВИДА СПОРТА (ВОДНОЕ ПОЛО)

В настоящем ученике представлены теоретические и практические разделы, которые позволяют студентам, обучающимся по специализации 61010300 Спортивная деятельность (водное поло). Для начального этапа развития водного поло, необходимо плавать, в связи с этим формируется техника плавания ватерполиста. Учебник рекомендован тренерам, преподавателям спортивных школ, в специализированных спортивных школах по водным видам спорта, в центрах подготовки Олимпииских и Параолимпийских видов спорта. Республиканской Школы Олимпийского Резерва, Университета физической культуры и спорта.

Fizika va agrometeorologiya

Mazkur darslikda agrometeorologik omillarning qishloq xo‘jaIigida ishlab chiqarish mahsuldorligiga ta’sirini meteorologiya va iqiimshunoshlikka bog'lagan holda keng bayon etilgan.

Fizikaviy kimyo

Darslikdan ishlab chiqarish texnologiyalari taʼlim sohasining boshqa taʼlim yoʻnalishlari boʻyicha taʼlim olayotgan talabalar, magistrantlar, ilmiy xodimlar va oʻqituvchilar ham foydalanishlari mumkin.

Кузнечное дело

В книге также освещаются вопросы организации труда.

Maxsus fanlarni o'qitish metodikasi

Darslik mazkur fanni o'rganishning nazariy va amaliy asoslarini qamrab olgan.

Anyone Can Code The Art and Science of Logical Creativity

Programming is about logical creativity, solving problems through logical thinking and design, and also formal methods of presenting those thoughts and solutions. In the first part of this book (Introduction, Chapters 1 and 2), I aim to provide some historical and background information on computer programming and introduce the basic concepts in logical creativity. This includes algorithmic thinking as the main approach to design and present solutions and programs that implement them.

Anyone Can Code. Algorithmic Thinking

I will never forget the blank look on some of my students' faces when they were given a programming task and simply stared at the screen not knowing how and where to start. It took me a while to realize the problem was not that the development tool they were using was not friendly or the programming language was too complex. They had a solution in their mind, and they could remember (or look up) the language syntax. But there was a link missing between what was in their mind and a working program. This book is about that missing link, Algorithmic Thinking; how to organize our thoughts into good algorithms that can be easily translated into good programs. In other terms, in order to write a program, we need to first come up with the right algorithm (step-by-step process that computer has to follow), and to design good algorithms, we need to think algorithmically.

Algorithmic Thinking. A Problem-Based Introduction

Algorithmic Thinking will teach you how to solve challenging programming problems and design your own algorithms. Daniel Zingaro, a master teacher, draws his examples from world-class programming competitions like USACO and IOI. You'll learn how to classify problems, choose data structures, and identify appropriate algorithms. You'll also learn how your choice of data structure, whether a hash table, heap, or tree, can affect runtime and speed up your algorithms; and how to adopt powerful strategies like recursion, dynamic programming, and binary search to solve challenging problems.

Algorithmic Mathematics in Machine Learning

In many branches of science, economy, and industry, the amount of available data has become immense during recent years. Most of these data do not contain any valuable information. However, the differentiation between useful data and “data waste” is seldom straightforward. Moreover, in applications where expensive (practical or numerical) experiments are involved in the data acquisition process, the available data sets are rather small. To meet the different challenges on real-world data sets, like, for example, describing useful information in a more compact format (dimensionality reduction) or making predictions on unseen data (regression), many different ideas and approaches have emerged. These are usually grouped together under the name machine learning (ML) methods.

A practical guide to building agents

Large language models are becoming increasingly capable of handling complex, multi-step tasks. Advances in reasoning, multimodality, and tool use have unlocked a new category of LLM-powered systems known as agents. This guide is designed for product and engineering teams exploring howto build their first agents, distilling insights from numerous customer deployments into practical and actionable best practices. It includes frameworks for identifying promising use cases, clear patterns for designing agent logic and orchestration, and best practices to ensure your agents run safely, predictably, and effectively. After reading this guide, you’ll have the foundational knowledge you need to confidently start building your first agent.