Название: Microeconometrics with R
Автор: Yves Croissant
Издательство: CRC Press
Серия: The R Series
Год: 2025
Страниц: 517
Язык: английский
Формат: pdf (true), epub
Размер: 14.9 MB

This book is about doing microeconometrics, defined by Cameron and Trivedi as "the analysis of individual-level data on the economic behavior of individuals or firms using regression methods applied to cross-section and panel data" with R. Microeconometrics became increasingly popular in the last decades, thanks to the availability of many individual data sets and to the development of computer performance. R appeared in the late nineties as a clone of S. It became increasingly popular among statisticians, especially in fields where S was widely used. Twenty years ago, using R for doing econometrics analysis required a lot of programming because a lot of core methods of econometrics were not available in R. Nowadays, most of the basic methods described in the book are available in contributed packages. Moreover, the set of packages called the Tidyverse developed by RStudio (now Posit) for all the basic tasks of an applied statistician (importing, tidying, transforming and visualizing data sets) makes the use of R faster and easier.

Название: Balancing Coupling in Software Design: Universal Design Principles for Architecting Modular Software Systems (Final)
Автор: Vlad Khononov
Издательство: Addison-Wesley/Pearson Education, Inc.
Год: 2025
Страниц: 320
Язык: английский
Формат: epub
Размер: 12.5 MB

Learn How Coupling Impacts Every Software Design Decision You Make--and How to Control It. If you want to build modular, evolvable, and resilient software systems, you have to get coupling right. Every design decision you make influences coupling, which in turn shapes the design options available to you. Despite its importance, coupling often doesn't receive the attention it deserves--until now. Since the dawn of software engineering, it's been clear that proper management of coupling is essential for architecting modular software systems. This topic has been extensively researched over the years, but some of that knowledge has been forgotten, and some of it is challenging to apply in this day and age. In Balancing Coupling in Software Design, author Vlad Khononov has built a model that not only draws on this accumulated knowledge, but also adapts it to modern software engineering practices, offering a fresh perspective on modular software design.

Название: Artificial Intelligence and Actuarial Science: Applications and Case Studies from Finance and Insurance
Автор: Sonal Trivedi, M.K. Nallakaruppan, Balamurugan Balusamy, Nithya Rekha Sivakumar
Издательство: CRC Press
Год: 2025
Страниц: 238
Язык: английский
Формат: pdf (true), epub
Размер: 12.2 MB

This book aims to explore how to automate, innovate, design, and deploy emerging technologies in actuarial work transformations for the insurance and finance sector. It examines the role of Artificial Intelligence with process automation in daily monitoring of solvency, governance, compliance, data processes, etc. It also explores the usage of machine learning, telematics system, AI-enabled claim processing software, Big Data and Algorithms, Explainable AI, and AI-enabled risk management tools in various actuarial processes. Actuarial work is being transformed by the integration of Artificial Intelligence (AI) and process automation. This book examines the role of AI with process automation in daily monitoring of solvency, governance, compliance, data processes, etc. It also explores the usage of Machine Learning (ML), telematics system, AI‑enabled claim processing software, Big Data and Algorithms, Explainable AI, and AI‑enabled risk management tools in various actuarial processes. This book covers a huge application of emerging technologies in the transformation of actuarial work in insurance, as well as almost all the areas where the various emerging cutting‑edge technologies can be applied in the actuarial process.

Название: We, Programmers: A Chronicle of Coders from Ada to AI (Final)
Автор: Robert C. Martin
Издательство: Pearson Education
Год: 2025
Страниц: 466
Язык: английский
Формат: epub
Размер: 14.0 MB

The Journey of Programming and Its Pioneers: From the Birth of Code to the Rise of AI. In We, Programmers, software legend Robert C. Martin--"Uncle Bob"--dives deep into the world of programming, exploring the lives of the groundbreaking pioneers who built the foundation of modern computing. From Charles Babbage and Ada Lovelace to Alan Turing, Grace Hopper, and Dennis Ritchie, Martin shines a light on the figures whose brilliance and perseverance changed the world. For programmers, coders, and anyone fascinated by the intersection of people and machines, this guide to the history, humanity, and technology behind the code that powers our world today is a fascinating and essential read.

Название: Power and Sample Size in R
Автор: Catherine M. Crespi
Издательство: CRC Press
Год: 2025
Страниц: 371
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB

Power and Sample Size in R guides the reader through power and sample size calculations for a wide variety of study outcomes and designs and illustrates their implementation in R software. It is designed to be used as a learning tool for students as well as a resource for experienced statisticians and investigators. The book begins by explaining the process of power calculation step by step at an introductory level and then builds to increasingly complex and varied topics. For each type of study design, the information needed to perform a calculation and the factors that affect power are explained. Concepts are explained with statistical rigor but made accessible through intuition and examples. The book demonstrates calculations in R using examples. Only a basic proficiency in R is assumed. We use functions from the powertools package, which was developed as a companion R package to this book, as well as other packages. There are many packages for various types of power and sample size calculations available in R, and we try to summarize available resources in each chapter. The index includes not only concepts and topics but also the R functions and packages mentioned in the book.

Название: Introduction to Artificial Intelligence 3rd Edition
Автор: Wolfgang Ertel
Издательство: Springer
Серия: Undergraduate Topics in Computer Science
Год: 2025
Страниц: 393
Язык: английский
Формат: pdf (true)
Размер: 12.9 MB

This accessible and engaging textbook presents a concise introduction to the exciting field of Artificial Intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, Machine Learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated third edition also includes new material on Deep Learning. Besides corrections of errors, this edition has new sections on data normalization, quality metrics for Machine Learning, data augmentation and a detailed introduction to convolutional networks, the now dominant technique of Deep Learning. Also new are an introduction to large language models such as ChatGPT and the GAN networks used for generative AI, followed by an assessment of how Deep Learning will change the world. Anyone who wants to put AI into practice should come equipped with firm knowledge of programming. Python is a useful language for this due to its relatively high level of abstraction and its many good libraries, particularly for Machine Learning.

Название: The Cybersecurity Trinity: Artificial Intelligence, Automation, and Active Cyber Defense
Автор: Donnie W. Wendt
Издательство: Apress
Год: 2024
Страниц: 406
Язык: английский
Формат: pdf
Размер: 16.7 MB

This book explores three crucial topics for cybersecurity professionals: Artificial Intelligence (AI), automation, and active cyber defense (ACD). The Cybersecurity Trinity will provide cybersecurity professionals with the necessary background to improve their defenses by harnessing the combined power of these three concepts. The book is divided into four sections, one addressing each underlying concept and the final section discussing integrating them to harness their full potential. With the expected growth of AI and Machine Learning (ML), cybersecurity professionals must understand its core concepts to defend AI and ML-based systems. Also, most cybersecurity tools now incorporate AI and ML. However, many cybersecurity professionals lack a fundamental understanding of AI and ML. The book's first section aims to demystify AI and ML for cybersecurity practitioners by exploring how AI and ML systems work, where they are vulnerable, and how to defend them.

Название: Applied Statistics: Methods Using R
Автор: Jürgen Hedderich, Lothar Sachs
Издательство: Springer
Год: 2024
Страниц: 1056
Язык: английский
Формат: pdf (true)
Размер: 22.8 MB

This standard work on statistical methods in life sciences and medicine provides easily understandable, illustrative, and practical guidance to students, lecturers and practitioners alike, covering all necessary methods for targeted and careful data collection, analysis, and evaluation. In addition to offering advice and recommendations on study planning and analysis, numerous examples, cross-references, further references and a detailed index provide a comprehensive approach to statistics. The consistent use of the freely available programming language R further facilitates the entry for curious users and practitioners. R is primarily a programming language and programming environment for the statistical analysis of data. R can perform elementary mathematical operations on the one hand, but on the other hand, it also calculates sophisticated complex statistical functions. The use of R is simple and largely intuitive. R shows great flexibility in dealing with statistical functions and can also be extended for special methods. The R program offers versatile possibilities for the graphical preparation of data and results.

Название: Generative AI: Current Trends and Applications
Автор: Khalid Raza, Naeem Ahmad, Deepak Singh
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2024
Страниц: 468
Язык: английский
Формат: pdf (true), epub
Размер: 43.5 MB

This comprehensive volume focuses on the latest advancements in Generative AI, including state-of-the-art techniques and models that are pushing the boundaries of what is possible. It covers recent developments in areas such as Generative AI models, transfer learning and Natural Language Processing (NLP) highlighting their potential to revolutionize content generation and creative applications including OpenAI, LangChain, NLTK and their practical implementations across diverse domains. The volume provides insights into emerging research areas, novel architectures, and innovative approaches in Generative AI, giving searchers a glimpse into the exciting future of the field. The aim is to offer readers a deep understanding of Generative AI and how it can be harnessed to tackle complex real-world challenges.

Название: Modern Business Analytics: Increasing the Value of Your Data with Python and R
Автор: Deanne Larson
Издательство: O’Reilly Media, Inc.
Год: 2025
Страниц: 560
Язык: английский
Формат: epub
Размер: 13.2 MB

Deriving business value from analytics is a challenging process. Turning data into information requires a business analyst who is adept at multiple technologies including databases, programming tools, and commercial analytics tools. This practical guide shows programmers who understand analysis concepts how to build the skills necessary to achieve business value. Author Deanne Larson, Data Science practitioner and academic, helps you bridge the technical and business worlds to meet these requirements. You'll focus on developing these skills with R and Python using real-world examples. You'll also learn how to leverage methodologies for successful delivery. Learning methodology combined with open source tools is key to delivering successful business analytics and value. The current trend in analytics is to use open source tools: the leading tools are Python and R. Python is a full programming language that covers the programming capabilities to complete the data engineering as well as the Machine Learning algorithms to create models. R is used for statistics and analysis with strong visualization capabilities. Both tools are fueled by the different packages and libraries available.