Название: Natural Language Generation
Автор: Ehud Reiter
Издательство: Springer
Год: 2025
Страниц: 208
Язык: английский
Формат: pdf (true), epub
Размер: 27.3 MB

In late 2022, the prominence of Natural Language Generation (NLG) surged with the advent of advanced language models like ChatGPT. While these developments have captivated both academic and commercial sectors, the focus has predominantly been on the latest innovations, often overlooking the rich history and foundational work in NLG. This book aims to provide a comprehensive overview of NLG, encompassing not only language models but also alternative approaches, user requirements, evaluation methods, safety and testing protocols, and practical applications. Natural Language Generation systems use Artificial Intelligence (AI) and natural language processing (NLP) techniques within software systems that generate texts in human languages such as English, Chinese, and Arabic. In other words, NLG is the science of AI systems that can write. As such it is related to (but not the same as) Natural Language Understanding (NLU), which is the science of AI systems that can read and extract meanings from human-written texts. Natural Language Generation has recently become more prominent because of the success of ChatGPT and other generative language models, but the field has been around for decades. AI and NLP techniques such as Machine Learning and language models are widely used, but they do not tell the whole story.

Название: Офисное программирование. Лабораторный практикум
Автор: Рутковская А. Э.
Издательство: РИПО
Год: 2017
Cтраниц: 149 с. : табл., ил.
Формат: pdf (ocr)
Размер: 36 мб
Язык: русский

Учебное пособие содержит лабораторно-практические работы по учебному предмету «Офисное программирование» и предусматривает закрепление теоретических знаний по темам: создание пользовательских процедур и функций, программирование вычислительных процессов, обработка массивов, использование математических функций, работа с записями, файлами, формами, основные понятия языка VBA в MS Excel и др.

Название: Groovy и Grails. Практические советы
Автор: Абдул-Джавад Б.
Издательство: ДМK
Год: 2010
Cтраниц: 408
Формат: pdf (ocr)
Размер: 41 мб
Язык: русский

Создание успешных корпоративных приложений на Java – сложная и трудоёмкая задача. Эта книга познакомит вас с технологиями Groovy и Grails, которые существенно упрощают разработку приложений. Материал преподносится в виде вопросов и ответов, что позволяет использовать книгу в качестве настольного руководства.

Название: Category Theory Using Haskell: An Introduction with Moggi and Yoneda
Автор: Shuichi Yukita
Издательство: Springer/Birkhäuser
Серия: Computer Science Foundations and Applied Logic
Год: 2025
Страниц: 301
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

This unique book offers an introductory course on category theory, which became a working language in algebraic geometry and number theory in the 1950s and began to spread to logic and Computer Science soon after it was created. Offering excellent use of helpful examples in Haskell, the work covers (among other things) concepts of functors, natural transformations, monads, adjoints, universality, category equivalence, and many others. The main goal is to understand the Yoneda lemma, which can be used to reverse-engineer the implementation of a function. Later chapters offer more insights into computer science, including computation with output, nondeterministic computation, and continuation passing. The work will be useful to undergraduate students in Computer Science who have enough background in college mathematics such as linear algebra and basics in Haskell polymorphic functions.

Название: Object-oriented programming for self-taught programmer
Автор: Terry Crummitt
Издательство: Independently published
Год: September 16, 2024
Язык: английский
Формат: epub
Размер: 12.8 MB

Object-Oriented Programming for Self-Taught Programmers: A Practical Guide to Mastering OOP Concepts! Are you a self-taught programmer looking to deepen your understanding of Object-Oriented Programming (OOP)? This book is designed specifically for you. "Object-Oriented Programming for Self-Taught Programmers" provides a clear and practical guide to mastering the core principles of OOP, offering real-world examples and step-by-step explanations. Whether you are transitioning from procedural programming or have dabbled in OOP concepts but struggled to grasp the full picture, this book will bridge the gap. With a focus on simplifying complex ideas, you'll learn how to structure code, build reusable components, and apply OOP techniques that will take your programming skills to the next level. No formal education? No problem. This guide is written for the self-motivated learner, offering a hands-on approach with practical coding examples to solidify your understanding.

Название: Statistical Quantitative Methods in Finance: From Theory to Quantitative Portfolio Management
Автор: Samit Ahlawat
Издательство: Apress
Год: 2025
Страниц: 301
Язык: английский
Формат: pdf (true)
Размер: 25.8 MB

Statistical quantitative methods are vital for financial valuation models and benchmarking Machine Learning models in finance. This book explores the theoretical foundations of statistical models, from ordinary least squares (OLS) to the generalized method of moments (GMM) used in econometrics. It enriches your understanding through practical examples drawn from applied finance, demonstrating the real-world applications of these concepts. Additionally, the book delves into non-linear methods and Bayesian approaches, which are becoming increasingly popular among practitioners thanks to advancements in computational resources. By mastering these topics, you will be equipped to build foundational models crucial for applied Data Science, a skill highly sought after by software engineering and asset management firms. These enhancements are illustrated through real-world examples from finance and econometrics, accompanied by Python code. This book assumes the reader is familiar with Python programming. Knowledge of libraries such as Statsmodels and Sklearn is not required. During the course of reading this book, the reader will acquire a synoptic understanding of frequently used APIs available for the model implementations supported by these libraries. For Data scientists, Machine Learning engineers, finance professionals, and software engineers.

Название: Introduction to Nonlinear Optimization: Theory, Algorithms, and Applications with Python and MATLAB, 2nd Edition
Автор: Amir Beck
Издательство: SIAM - Society for Industrial and Applied Mathematics
Год: 2023
Страниц: 365
Язык: английский
Формат: pdf
Размер: 23.7 MB

Built on the framework of the successful first edition, this book serves as a modern introduction to the field of optimization. The author’s objective is to provide the foundations of theory and algorithms of nonlinear optimization as well as to present a variety of applications from diverse areas of applied sciences. Introduction to Nonlinear Optimization gradually yet rigorously builds connections between theory, algorithms, applications, and actual implementation. The book contains several topics not typically included in optimization books, such as optimality conditions in sparsity constrained optimization, hidden convexity, and total least squares. Readers will discover a wide array of applications such as circle fitting, Chebyshev center, the Fermat–Weber problem, denoising, clustering, total least squares, and orthogonal regression. These applications are studied both theoretically and algorithmically, illustrating concepts such as duality. Python and MATLAB programs are used to show how the theory can be implemented. The extremely popular CVX toolbox (MATLAB) and CVXPY module (Python) are described and used. More than 250 theoretical, algorithmic, and numerical exercises enhance the reader's understanding of the topics. (More than 70 of the exercises provide detailed solutions, and many others are provided with final answers.) The theoretical and algorithmic topics are illustrated by Python and MATLAB examples.

Название: Introduction to Data Science Using Python
Автор: Afrand Agah
Издательство: PA-ADOPT
Год: 2024
Страниц: 117
Язык: английский
Формат: pdf (true), epub
Размер: 12.1 MB

This book contains two parts, the first is designed to be used in an introductory programming course for students looking to learn Python, without having any prior experience with programming. Basic programming concepts are discussed, explained, and illustrated with a Python program. Ample programming questions are provided for practice. The second part of the book utilizes Machine Learning concepts and statistics to accomplish data-driven resolutions. Python programs are provided to apply scientific computing to conclude statistically driven results. Data Science is the process of representing models that fit data. Its goal is to predict future output based on past observations of inputs. In Data Science, one collects information and interprets it to make decisions. Python is a popular programming language because of its scalability, readability, and strong community support. But perhaps the most important aspect is its extensive libraries and frameworks.

Название: Statistical Modeling and Computation, 2nd Edition
Автор: Joshua C.C. Chan, Dirk P. Kroese
Издательство: Springer
Год: 2025
Страниц: 497
Язык: английский
Формат: pdf (true)
Размер: 12.1 MB

This book, Statistical Modeling and Computation, provides a unique introduction to modern statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of mathematical statistics and modern statistical computation, emphasizing statistical modeling, computational techniques, and applications. Because not all readers will have access to MATLAB, we have switched in this Second Edition to the Julia programming language, which is freely available and is very close in syntax to MATLAB. For all examples with computing components, the authors provide data sets and their own Julia codes. In addition, being a compiled language, Julia is computationally significantly faster than R. The book is accompanied by the website from which the Julia code and data files can be downloaded. In addition, we provide MATLAB and R versions for each Julia program. To keep the book fully self-contained, we include the more technical proofs and mathematical theory in an appendix. To facilitate the use of Julia we have added a concise introduction to the Julia computing language.

Название: An Introduction to Python Jupyter Notebooks for College Math Teachers
Автор: Paul Isihara, Claire Wagner, Peter Jantsch, Thomas VanDrunen
Издательство: Wheaton College
Год: Jul 26, 2024
Страниц: 1191
Язык: английский
Формат: pdf (true)
Размер: 53.2 MB

This book is an introduction to the use of Python Jupyter Notebooks (JNBs) for college math teachers and their students. The book is an evolving work in progress, but we hope this 1st Edition may already be quite useful to a college math teacher who is interested to use Jupyter Notebooks in their courses. Each section of the book has been written in the form of a Jupyter Notebook and can be downloaded using the download button at the top menu bar. In some cases, additional data files or image files may need to be downloaded as well. Each chapter contains a JNB lab with solutions. Experienced teachers can modify these labs and create new labs tailored to their courses. The chapters were written by different authors/authorship teams, and as such, vary in style. Each chapter essentially can be read independently of the others as long as one has the pre-requisite mathematical knowledge. Some effort has been made to standardize the chapter formats, and the index may help the reader find specific topics of interest.