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

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.

UMUMIY PSIXOLOGIYA

Umumiy psixologiya darsligi inson shaxsidagi psixologik xolatlar, xususiyatlar, jarayonlar haqidagi dastlabki bilimlar majmuasini berishga qaratilgan. Darslik psixologiyaga kirish, muloqot, faoliyat, shaxs, bilish jarayonlari shaxsning hissiy-irodaviy motivatsion sohasi, shaxsning individualpsixologik xususiyatlari nomli bo'limlardan iborat. Psixologiyaga kirish qismida psixologiyaning predmeti, hozirgi zamon psixologiyasining tuzilishi va tadqiqot metodlari, psixiki va ongning taraqqiyoti mavzulari, ikkinchi bo'limda muloqot, faoliyat, shaxs mavzulari, bilish jarayonlari bo'limida diqqat, sezgi, idrok, xotira, tafakkur, xayol mavzulari, shaxsning hissiy-irodaviy motivasion sohasi bo'limida hisiyot, iroda, motivasiya mavzulari, shaxsning individual psixologik xususiyatlari bo'limida xarakter, temperament, qobiliyat mavzulariga doir ma'ruza matnlari, mavzular yuzasidan test topshiriqlari, shuningdek mustaqil ishlash uchun mavzular va adabiyotlar ro'yxati, nazorat savollaridan iborat. Shuningdek nazariy materiallarni yaqqol ifodalash maqsadida chizma grafik, jadvallardan foydalanilgan. Darslikdan oliy o'quv yurtlari pedagogika va psixologiya yo'nalishi boʻyicha ta'lim olayotgan talabalar, magistrantlar, o'qituvchilar, ilmiy xodimlar, umuman shu sohaga qiziqqan keng kitobxonlar ommasi foydalanishlari mumkin.

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).

Инглиз ва узбек тиллари киёсий грамматикаси.

Кулингиздаги дарслик китоби педагогика институтлари ва факультетларининг чет эл тилини урганувчи студентлари, икки тил системасини чогиштириш масалаларига кизикувчилар, аспирантлар, шунингдек, укитувчилар учун мулжалланган.

Data Science with R

The aim of this chapter is to introduce Data Mining and Knowledge Discovery in Databases. First, some basic concepts are defined along with the reasons why this scientific field was created and expanded rapidly. Second, we will review some practical examples and counterexamples of Data Mining. Additionally, the most important fields on which Data Mining is based are presented. Last, we will find out what R programming language is and its general philosophy. We will also show how to install all necessary tools, we will present how to address to the R language manual for help, and define its basic types and functions, along with their functionality.

Data Management at Scale. Modern Data Architecture with Data Mesh and Data Fabric

Data management is an emerging and disruptive subject. Datafication is everywhere. This transformation is happening all around us: in smartphones, TV devices, ereaders, industrial machines, self-driving cars, robots, and so on. It's changing our lives at an accelerating speed. As the amount of data generated skyrockets, so does its complexity. Disruptive trends like cloudification, API and ecosystem connectivity, microservices, open data, software as a service (SaaS), and new software delivery models have a tremendous effect on data management. In parallel, we see an enormous number of new applications transforming our businesses. All these trends are fragmenting the data landscape.