Litgu.ru - Литературный Гуру

Название: Рельефные узоры спицами
Автор: Галина Парахонько
Издательство: аст
Год: 2023
Формат: PDF
Страниц: 82
Размер: 19 Mb
Язык: Русский

В этой книге собрана авторская коллекция из 47 рельефных узоров: подводное царство, лестница в небо, загадочные пирамиды, нежная мандала – что скрывают эти названия? Берите спицы и пряжу и начинайте творить. Фотографии узоров, схемы и описания помогут быстро и легко связать всю коллекцию.

Название: Скетчбук по рисованию фэнтези
Автор: Анна Николаева
Издательство: Бомбора
Год: 2023
Формат: PDF
Страниц: 131
Размер: 17 Mb
Язык: Русский

Скетчбук по рисованию фэнтези – компактный самоучитель, который расскажет каждому, как красиво изображать любимые фэнтези-миры, от удивительных существ до магического сеттинга. Пошаговые мастер-классы просто и доступно научат самостоятельно рисовать эльфов, ведьм и других созданий, работать с разными фигурами и предметами и экспериментировать с ракурсами.

Название: The AI Revolution in Customer Service and Support (Early Release)
Автор: Ross Smith, Emily McKeon, Mayte Gonzalez
Издательство: Addison-Wesley Professional/Pearson Education
Год: 2024
Страниц: 409
Язык: английский
Формат: pdf, epub
Размер: 10.3 MB

Generative AI has made amazing advances in the last year, and customer service and support is one of the most important areas where this new technology can have an immediate impact. While the technology is not yet in a place where it will fully replace agents and support engineers, it can do wonders to dramatically improve customer experience while also contribute to the optimization of productivity in various ways. This book help readers understand how and where to incorporate AI technology into the flow of the customer experience. In the 2020s and beyond, AI is entering a new frontier of generative technologies, which aim to create novel and realistic content, such as images, texts, sounds, and videos. Generative technologies use deep learning models, such as generative adversarial networks (GANs), variational autoencoders (VAEs), and large language models (LLMs), to generate content that is indistinguishable from human-produced content. Generative technologies have various applications, such as art, entertainment, education, and communication. One of the most exciting and challenging areas of generative technologies is natural language generation (NLG), which generates natural language text from a given input, such as an image, a keyword, or a prompt. Some of the most notable and influential LLMs include GPTs, BERT, XLNet, T5, and DALL-E, which have been developed and released by leading research labs and companies, such as OpenAI, Google, Facebook, and Microsoft. LLMs have also enabled and inspired the creation and innovation of various applications and products, such as chatbots, assistants, recommender systems, content generators, summarizers, translators, analyzers, or synthesizers, which have been deployed and adopted by various industries and sectors, such as education, health, business, media, entertainment, or art, among others.

Название: Балканский гамбит. Тайный наследник
Автор: Алекс Хай
Издательство: СИ
Год: 2024
Формат: fb2, rtf
Размер: 10 Мб
Качество: Хорошее
Язык: Русский

Балы, красавицы, лакеи, юнкера? Черта с два! Ракия на завтрак, недоступные княжны, вековая кровная вражда и кофе, от крепости которого глаза лезут на лоб.
Мой дух призвали в тело молодого княжича из сербского рода, который все считают вымершим. Я должен отобрать корону Сербии у давних врагов, что убили моих предков и узурпировали власть. Но это не единственная моя проблема...

Название: Обработка текстовой и графической информации
Автор: Гарифуллин М. Ф.
Издательство: Техносфера
Год: 2019
Cтраниц: 174 с. : ил., схем.
Формат: pdf (ocr)
Размер: 26 мб
Язык: русский

Рассмотрены способы обработки текстовой и графической информации. Уделено внимание вопросам сортировки текстовых данных, построения и сканирования графиков, поддержки диалогового режима работы, создания и систематизации графических файлов. Приведены примеры текстов программ на языке FORTRAN с подробными комментариями.

Название: Экономико-математические методы и модели: компьютерное моделирование
Автор: Орлова И.В., Половников В.А.
Издательство: М.: Вузовский учебник
Год: 2007
Cтраниц: 365
Формат: pdf
Размер: 15 мб
Язык: русский

Рассмотрены задачи математического моделирования экономических процессов на базе компьютерных технологий подготовки и принятия решений. В качестве инструментального средства моделирования используется стандартная офисная программа Excel.

Название: Search Methods in Artificial Intelligence
Автор: Deepak Khemani
Издательство: Cambridge University Press
Год: 2024
Страниц: 488
Язык: английский
Формат: pdf
Размер: 11.3 MB

This book is designed to provide in-depth knowledge on how search plays a fundamental role in problem solving. Meant for undergraduate and graduate students pursuing courses in Computer Science and Artificial Intelligence, it covers a wide spectrum of search methods. Readers will be able to begin with simple approaches and gradually progress to more complex algorithms applied to a variety of problems. It demonstrates that search is all pervasive in Artificial Intelligence and equips the reader with the relevant skills. This book is meant for the serious practitioner-to-be of constructing intelligent machines. Machines that are aware of the world around them, that have goals to achieve, and the ability to imagine the future and make appropriate choices to achieve those goals. It is an introduction to a fundamental building block of Artificial Intelligence (AI). As the book shows, search is central to intelligence. A neuron is a simple device that computes a simple function of the inputs it receives. Collections of interconnected neurons can do complex computations. Insights into animal brains have prompted many researchers to pursue the path of creating artificial neural networks (ANNs). An ANN is a computational model that can be trained to perform certain tasks by repeatedly showing a stimulus and the expected response. Deep networks got further impetus with the availability of open source software like Tensorflow from Google that makes the task of implementing Machine Learning models easier for researchers. More recently, generative neural networks have been successfully deployed for language generation and even creating paintings, for example, from OpenAI. Generative models embody a form of unsupervised learning from large amounts of data, and are then trained to generate data like the one the algorithms were trained on.

Название: The French School of Programming
Автор: Bertrand Meyer
Издательство: Springer
Год: 2024
Страниц: 451
Язык: английский
Формат: pdf (true)
Размер: 11.9 MB

The French School of Programming is a collection of insightful discussions of programming and software engineering topics, by some of the most prestigious names of French Computer Science. The authors include several of the originators of such widely acclaimed inventions as abstract interpretation, the Caml, OCaml and Eiffel programming languages, the Coq proof assistant, agents and modern testing techniques. The book is divided into four parts, reflecting the diversity of interests in the French community and each of them corresponding to an area in which it has made major contributions over several decades: • Software engineering (Part I); • Programming language mechanism and type systems (Part II); • Theory (Part III); • Language design and programming methodology (Part IV). Object-oriented programming, software components and multi-agent systems are some examples of approaches for software design and development with significant impact. Both offer abstractions for organizing software as a combination of software elements, with a common objective of facilitating its evolution (first of all, replacement and addition of elements).

Название: An Introduction to Spatial Data Science with GeoDa, Volume 1: Exploring Spatial Data
Автор: Luc Anselin
Издательство: CRC Press
Год: 2024
Страниц: 453
Язык: английский
Формат: pdf (true)
Размер: 20.4 MB

This book is the first in a two-volume series that introduces the field of Spatial Data Science. It offers an accessible overview of the methodology of exploratory spatial data analysis. It also constitutes the definitive user’s guide for the widely adopted GeoDa open-source software for spatial analysis. Leveraging a large number of real-world empirical illustrations, readers will gain an understanding of the main concepts and techniques, using dynamic graphics for thematic mapping, statistical graphing, and, most centrally, the analysis of spatial autocorrelation. Key to this analysis is the concept of local indicators of spatial association, pioneered by the author and recently extended to the analysis of multivariate data. The focus of the book is on intuitive methods to discover interesting patterns in spatial data. It offers a progression from basic data manipulation through description and exploration to the identification of clusters and outliers by means of local spatial autocorrelation analysis. A distinctive approach is to spatialize intrinsically non-spatial methods by means of linking and brushing with a range of map representations, including several that are unique to the GeoDa software. The book also represents the most in-depth treatment of local spatial autocorrelation and its visualization and interpretation by means of GeoDa. The libgeoda library has a clearly defined Application Programming Interface (API), which allows other C++ code to access its functionality directly. In fact, this is what currently happens under the hood for part of desktop GeoDa, and in the experimental web-GeoDa (jsgeoda, implemented through jаvascript). In addition to achieving a more flexible interaction with different graphical user interface implementations, the API also allows other software, such as R or Python programs to access the functionality through well-defined wrapper code.

Название: An Introduction to Spatial Data Science with GeoDa: Volume 2: Clustering Spatial Data
Автор: Luc Anselin
Издательство: CRC Press
Год: 2024
Страниц: 238
Язык: английский
Формат: pdf (true)
Размер: 34.7 MB

This book is the second in a two-volume series that introduces the field of spatial Data Science. It moves beyond pure data exploration to the organization of observations into meaningful groups, i.e., spatial clustering. This constitutes an important component of so-called Unsupervised Learning, a major aspect of modern Machine Learning. The distinctive aspects of the book are both to explore ways to spatialize classic clustering methods through linked maps and graphs, as well as the explicit introduction of spatial contiguity constraints into clustering algorithms. Leveraging a large number of real-world empirical illustrations, readers will gain an understanding of the main concepts and techniques and their relative advantages and disadvantages. The book also constitutes the definitive user’s guide for these methods as implemented in the GeoDa open source software for spatial analysis. It is organized into three major parts, dealing with dimension reduction (principal components, multidimensional scaling, stochastic network embedding), classic clustering methods (hierarchical clustering, k-means, k-medians, k-medoids and spectral clustering), and spatially constrained clustering methods (both hierarchical and partitioning). It closes with an assessment of spatial and non-spatial cluster properties.