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

O‘zbckiston tarixi

Darslikda V atanim izning qadim zam onlardan to hozirgi davrgacha o'tgan bir necha ming villik tarixi oliy o'quv yurtlari uchun tavsiya etilgan " 0 ‘zbekiston tarixi" o ‘quv dasturi talablari doirasida yoritilgan.

Немис тили фонетикаси.

Мазкур кулланма республика университетлари, педагогика институтлари чет тиллар факультетларининг I - II курс талабаларига мулжалланган.

Elasticsearch: A Complete Guide. End-to-end Search and Analytics A course in three modules

Module 1, Elasticsearch Essentials, this module provides a complete coverage of working with Elasticsearch using Python and as well as Java APIs to perform CRUD operations, aggregation-based analytics, handling document relationships, working with geospatial data, and controlling search relevancy. Module 2, Mastering Elasticsearch, in this module we start with an introduction to the world of Lucene and Elasticsearch. We will discuss topics such as different scoring algorithms, choosing the right store mechanism, what the differences between them are, and why choosing the proper one matters. We touch the administration part of Elasticsearch by discussing discovery and recovery modules and the human-friendly Cat API.

Effective .NET Memory Management

In the dynamic world of software development, memory management is a critical yet often overlooked subject that significantly impacts the performance and reliability of applications. As developers, we are constantly seeking ways to optimize our code, reduce resource consumption, and enhance the efficiency of our applications. .NET, with its advanced garbage collection and memory allocation mechanisms, provides a robust environment for building high-performance applications. Still, it also requires a deep understanding of memory management to fully harness its potential.

Demystifying Deep Learning. An Introduction to the Mathematics of Neural Networks

Interest in deep learning (DL) is increasing every day. It has escaped from the research laboratories and become a daily fact of life. The achievements and potential of DL are reported in the lay news and form the subject of discussion at dinner tables, cafes, and pubs across the world. This is an astonishing change of fortune considering the technology upon which it is founded was pronounced a research dead end in 1969 (131) and largely abandoned. The universe of DL is a veritable alphabet soup of bewildering acronyms. There are artificial neural networks (ANN)s, RNNs, LSTMs, CNNs, Generative Adversarial Networks (GAN)s, and more are introduced every day. The types and applications of DL are proliferating rapidly, and the acronyms grow in number with them. As DL is successfully applied to new problem domains this trend will continue. Since 2015 the number of artificial intelligence (AI) patents filed per annum has been growing at a rate of 76.6% and shows no signs of slowing down (169). The growth rate speaks to the increasing investment in DL and suggests that it is still accelerating.

Deep Learning for Multimedia Processing Applications

Deep Learning for Multimedia Processing is a comprehensive guide that explores the revolutionary impact of deep learning techniques in the field of multimedia processing. Written for a wide range of readers, from students to professionals, this book offers a concise and accessible overview of the application of deep learning in various multimedia domains, including image processing, video analysis, audio recognition, and natural language processing. Divided into two volumes, Volume One begins by introducing the fundamental concepts of deep learning, providing readers with a solid foundation to understand its relevance in multimedia processing. Volumes Two delves into advanced topics such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs), explaining their unique capabilities in multimedia tasks. Readers will discover how deep learning techniques enable accurate and efficient image recognition, object detection, semantic segmentation, and image synthesis. The book also covers video analysis techniques, including action recognition, video captioning, and video generation, highlighting the role of deep learning in extracting meaningful information from videos.

Немис тили грамматикаси

Мазкур дарслик "Укитувчи нашриётида 1974 йилда чоп этилган Т.З.Мирсоатовнинг "Немис тили грамматикаси" (морфология) кулланмасининг амалдаги программага мувофик кайта ишланган ва тулдирилган нашридир.

Deciphering Data Architectures. Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh

Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of these architectures to help data professionals understand the pros and cons of each. James Serra, big data and data warehousing solution architect at Microsoft, examines common data architecture concepts, including how data warehouses have had to evolve to work with data lake features. You'll learn what data lakehouses can help you achieve, as well as how to distinguish data mesh hype from reality. Best of all, you'll be able to determine the most appropriate data architecture for your needs.

Word Wise

Бу дарслик инглиз тилини урганувчиларга мустакил ишлаш куникмаларини ва мутолаа малакаларини хосил килишда узининг ижобий улушини кушишга мулжалланган.

Data Structures and Other Objects Using C++

This book is written for a second course in computer science, the CS 2 course at many universities. The text's emphasis is on the specification, design, implementation, and use of the basic data types that normally are covered in a second-semester course. In addition, we cover a range of important programming techniques and provide self-contained coverage of abstraction techniques, object-oriented programming, big-O time analysis of algorithms, and sorting.

Data Structures And Algorithms Made Easy In JAVA Data Structures and Algorithmic Puzzles

The objective of this chapter is to explain the importance of the analysis of algorithms, their notations, relationships and solving as many problems as possible. Let us first focus on understanding the basic elements of algorithms, the importance of algorithm analysis, and then slowly move toward the other topics as mentioned above. After completing this chapter, you should be able to find the complexity of any given algorithm (especially recursive functions).

English conversation book. Инглизча сузлашув китоби.

Инглизча - узбекча сузлашув китоби узбек мактабларининг V - Х синф укувчилари учун мулжалланган.

Biologiya 11-Sinf

Hozirgi paytda insoniyat oldida turgan muhim vazifalardan biri tabiatdagi biolo gik xilma-xillikni asrash, ekologik barqarorlikni ta’minlash, global iqlim o‘zgarishlarining salbiy ta’sirini yumshatish sanaladi. Inson salomatligiga tahdid sola yotgan allergik, yuqumli va epidemiologik kasalliklarning oldini olish, qishloq xo‘jaligini modernizatsiya qilish va jadal rivojlantirish, ekologik toza mahsulotlar ishlab chiqarishni kengaytirish, sug‘oriladigan yerlarning meliorativ holatini yanada yaxshilash, suv va boshqa resurslarni tejaydigan zamonaviy agrotexnologiyalarni joriy etish zarur.

MEVA-SABZAVOTCHILIK

Sabzavot ekinlarining ayrimlari tarkibida achchiq fiton- sidlarni saqlab, ular inson organizmini sog‘lomlashtirishga xizrnat qiladi, bularga: piyoz, sarimsoq piyoz, shivit, kashnich, selderey, xren va boshqalar kiradi. Ayrimlari xushbo‘y efir moylarini saqlab ishtaxani ochib, ovqatning tez hazm boMishiga yordam beradi. Ayrimlari o‘ta ko‘p miqdorda kraxmal, qand, kletchatka saqlaydi.

English. Инглиз тили грамматикаси.

Педагогика олий укув юртлари гуманитар факультетларининг I - II курс талабаларига мулжалланган мазкур дарслик амалдаги дастур (программа) асосида ёзилган.

Tabiiy fanlar I-qism 3-sinf

3-sinf o'quvchilari uchun mo`ljallangan darslik.