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Introduction to Responsible AI, Manure


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Автор: Manure
Название:  Introduction to Responsible AI
ISBN: 9781484299814
Издательство: Springer
Классификация:


ISBN-10: 1484299817
Обложка/Формат: Soft cover
Страницы: 184
Вес: 0.31 кг.
Дата издания: 07.12.2023
Язык: English
Издание: 1st ed.
Иллюстрации: 18 illustrations, black and white; ix, 184 p. 18 illus.
Размер: 154 x 235 x 15
Основная тема: Computer Science
Подзаголовок: Implement ethical ai using python
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: Learn and implement responsible AI models using Python. This book will teach you how to balance ethical challenges with opportunities in artificial intelligence. The book starts with an introduction to the fundamentals of AI, with special emphasis given to the key principles of responsible AI. The authors then walk you through the critical issues of detecting and mitigating bias, making AI decisions understandable, preserving privacy, ensuring security, and designing robust models. Along the way, you’ll gain an overview of tools, techniques, and code examples to implement the key principles you learn in real-world scenarios. The book concludes with a chapter devoted to fostering a deeper understanding of responsible AI’s profound implications for the future. Each chapter offers a hands-on approach, enriched with practical insights and code snippets, enabling you to translate ethical considerations into actionable solutions. What You Will Learn * Understand the principles of responsible AI and their importance in todays digital world * Master techniques to detect and mitigate bias in AI * Explore methods and tools for achieving transparency and explainability * Discover best practices for privacy preservation and security in AI * Gain insights into designing robust and reliable AI models Who This Book Is For AI practitioners, data scientists, machine learning engineers, researchers, policymakers, and students interested in the ethical aspects of AI
Дополнительное описание: Chapter 1: Introduction.- Chapter 2: Bias and Fairness.- Chapter 3: Transparency and Explainability.- Chapter 4: Privacy and Security.- Chapter 5: Ensuring Robustness and Reliability.- Chapter 6: Conclusion.



Introduction to statistical learning

Автор: James, Gareth Witten, Daniela Hastie, Trevor Tibsh
Название: Introduction to statistical learning
ISBN: 1071614177 ISBN-13(EAN): 9781071614174
Издательство: Springer
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Цена: 7317.00 р.
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Описание: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more.

Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers.

An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naive Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

Introduction to Functional Programming Systems Using Haskell

Автор: Davie
Название: Introduction to Functional Programming Systems Using Haskell
ISBN: 0521277248 ISBN-13(EAN): 9780521277242
Издательство: Cambridge Academ
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Цена: 7445.00 р.
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Описание: An introduction to functional programming and its associated systems. A unique feature is its use of the language Haskell for teaching both the rudiments and the finer points of the functional technique. It serves as an introduction both to functional programming and Haskell. Especially valuable are the chapters on programming and implementation, along with a large number of exercises.

Responsible Artificial Intelligence

Автор: Schmidpeter, Rene
Название: Responsible Artificial Intelligence
ISBN: 3031092449 ISBN-13(EAN): 9783031092442
Издательство: Springer
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Цена: 7927.00 р.
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Описание: Artificial intelligence - and social responsibility. Two topics that are at the top of the business agenda. This book discusses in theory and practice how both topics influence each other. In addition to impulses from the current often controversial scientific discussion, it presents case studies from companies dealing with the specific challenges of artificial intelligence. Particular emphasis is placed on the opportunities that artificial intelligence (AI) offers for companies from different industries. The book shows how dealing with the tension between AI and challenges caused by new corporate social responsibility creates strategic opportunities and also innovation opportunities. It highlights the active involvement of stakeholders in the design process, which is meant to build trust among customers and the public and thus contributes to the innovation and acceptance of artificial intelligence. The book is aimed at researchers and practitioners in the fields of corporate social responsibility as well as artificial intelligence and digitalization. The chapter "Exploring AI with purpose" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Intelligent Road Transport Systems

Автор: WANG
Название: Intelligent Road Transport Systems
ISBN: 9811657750 ISBN-13(EAN): 9789811657757
Издательство: Springer
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Цена: 20733.00 р.
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Описание: In recent years, the application of intelligent transportation systems (ITS) has steadily expanded, and has become a hot spot of common interest to universities, scientific research institutes, enterprises and institutions in the transportation field. ITS is the product of the deep integration of modern high-tech in the transportation industry, and its development has accompanied that of modern high-tech. ITS is now also becoming part of the Internet of Things (IoT), and is expected to contribute significantly to making our cities smarter and connecting with other infrastructure. Although there are many monographs and textbooks on intelligent transportation, with the advancement of technology and changes in demand, the key technologies of ITS are also rapidly changing. This book chiefly focuses on the main technologies of ITS, examining them from four perspectives: “sense” (perception and management of traffic information, chapters 2 & 3), “transmission” (interaction of traffic information, chapter 4), “prediction” (prediction of traffic states, chapter 6) and “application” (intelligent transportation applications, chapters 6 through 10). Given its scope, the book can be used as a textbook for undergraduates or graduates, as well as a reference book for research institutes and enterprises. This book emphasizes the use of basis traffic engineering principles and state-of-art methodologies to develop functional designs. It largely reflects the authors’ own experience in adapting these methodologies to ITS design. For example, the book addresses various forms of data collection, models used to predict and evaluate traffic states, comprehensive description in connected vehicles, applications for users and traffic managers, etc. The knowledge gained here will allow designers to estimate the performance differences among alternatives and gauge their potential benefits for functional design purposes. To gain the most from the book, readers should be somewhat familiar with the field of traffic engineering and interested in ITS.

Introduction to mathematical models in operations planning

Автор: Tayali, Halit Alper (istanbul Universitesi)
Название: Introduction to mathematical models in operations planning
ISBN: 1032191996 ISBN-13(EAN): 9781032191997
Издательство: Taylor&Francis
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Цена: 8879.00 р.
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Apply Data Science

Автор: Thomas Barton
Название: Apply Data Science
ISBN: 3658387971 ISBN-13(EAN): 9783658387976
Издательство: Springer
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Цена: 6097.00 р.
Наличие на складе: Нет в наличии.

Описание: This book offers an introduction to the topic of data science based on the visual processing of data. It deals with ethical considerations in the digital transformation and presents a process framework for the evaluation of technologies. It also explains special features and findings on the failure of data science projects and presents recommendation systems in consideration of current developments. Machine learning functionality in business analytics tools is compared and the use of a process model for data science is shown. The integration of renewable energies using the example of photovoltaic systems, more efficient use of thermal energy, scientific literature evaluation, customer satisfaction in the automotive industry and a framework for the analysis of vehicle data serve as application examples for the concrete use of data science. The book offers important information that is just as relevant for practitioners as for students and teachers.

Principles of Responsible Management Education (PRME) in the Age of Artificial Intelligence (AI) - Opportunities, Threats, and the Way Forward

Автор: Stachowicz-Stanusch Agata, Amann Wolfgang, Sharma Radha
Название: Principles of Responsible Management Education (PRME) in the Age of Artificial Intelligence (AI) - Opportunities, Threats, and the Way Forward
ISBN: 1648025447 ISBN-13(EAN): 9781648025440
Издательство: Mare Nostrum (Eurospan)
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Цена: 21784.00 р.
Наличие на складе: Нет в наличии.

Описание: Authored by a range of international experts, this book brings us closer to the responses for the questions like how may AI be used /or is a threat for PRME implementation, how will AI impact the business education world or what we should teach in business school in the time of AI (what the`right` set of future skills is)?

Data science

Автор: Timbers, Tiffany-anne (university Of British Colum
Название: Data science
ISBN: 0367524686 ISBN-13(EAN): 9780367524685
Издательство: Taylor&Francis
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Цена: 7501.00 р.
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Описание: Data Science: An Introduction focuses on using the R programming language in Jupyter notebooks to perform basic data manipulation and cleaning, create effective visualizations, and extract insights from data using supervised predictive models.

An Introduction to Data: Everything You Need to Know about Ai, Big Data and Data Science

Автор: Corea Francesco
Название: An Introduction to Data: Everything You Need to Know about Ai, Big Data and Data Science
ISBN: 303004467X ISBN-13(EAN): 9783030044671
Издательство: Springer
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Цена: 18294.00 р.
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Описание: This book reflects the author’s years of hands-on experience as an academic and practitioner. It is primarily intended for executives, managers and practitioners who want to redefine the way they think about artificial intelligence (AI) and other exponential technologies. Accordingly the book, which is structured as a collection of largely self-contained articles, includes both general strategic reflections and detailed sector-specific information. More concretely, it shares insights into what it means to work with AI and how to do it more efficiently; what it means to hire a data scientist and what new roles there are in the field; how to use AI in specific industries such as finance or insurance; how AI interacts with other technologies such as blockchain; and, in closing, a review of the use of AI in venture capital, as well as a snapshot of acceleration programs for AI companies.

Introduction to multiagent systems

Автор: Wooldridge, Michael
Название: Introduction to multiagent systems
ISBN: 0470519460 ISBN-13(EAN): 9780470519462
Издательство: Wiley
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Цена: 9021.00 р.
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Описание: The eagerly anticipated updated resource on one of the most important areas of research and development: multi-agent systems Multi-agent systems allow many intelligent agents to interact with each other, and this field of study has advanced at a rapid pace since the publication of the first edition of this book, which was nearly a decade ago.

The Student`s Introduction to Mathematica and the Wolfram Language

Автор: Bruce F. Torrence, Eve A. Torrence
Название: The Student`s Introduction to Mathematica and the Wolfram Language
ISBN: 110840636X ISBN-13(EAN): 9781108406369
Издательство: Cambridge Academ
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Цена: 7762.00 р.
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Описание: This book introduces Mathematica (R) and the Wolfram Language (TM) in the context of the standard university mathematics curriculum. It equips current and former students to harness these tools to explore ideas from pre-calculus, calculus, and linear algebra. Additional chapters on programming and 3D printing provide outlets for further exploration.

Introduction to Computational Economics Using Fortran

Автор: Fehr Hans
Название: Introduction to Computational Economics Using Fortran
ISBN: 0198850379 ISBN-13(EAN): 9780198850373
Издательство: Oxford Academ
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Цена: 7869.00 р.
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Описание: This exercise and solutions manual accompanies the main edition of Introduction to Computational Economics Using Fortran. It enables students of all levels to practice the skills and knowledge needed to conduct economic research using Fortran.


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