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Author: Nelson Goodman
Publisher:
ISBN: 9780748603510
Category : Philosophy
Languages : en
Pages : 292
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Book Description
How Classification Works attempts to bridge the gap between philosophy and the social sciences using as a focus some of the work of Nelson Goodman. Throughout his long career Goodman has addressed the question: are some ways of conceptualizing more natural than others? This book looks at the rightness of categories, assessing Goodman's role in modern philosophy and explaining some of his ideas on the relation between aesthetics and cognitive theory. Two papers by Nelson Goodman are included in the collection and there are analyses of his work by seven leading academics in anthropology, philosophy, sociology and musicology.
Author: Nelson Goodman
Publisher:
ISBN: 9780748603510
Category : Philosophy
Languages : en
Pages : 292
Get Book Here
Book Description
How Classification Works attempts to bridge the gap between philosophy and the social sciences using as a focus some of the work of Nelson Goodman. Throughout his long career Goodman has addressed the question: are some ways of conceptualizing more natural than others? This book looks at the rightness of categories, assessing Goodman's role in modern philosophy and explaining some of his ideas on the relation between aesthetics and cognitive theory. Two papers by Nelson Goodman are included in the collection and there are analyses of his work by seven leading academics in anthropology, philosophy, sociology and musicology.
Author: Leo Breiman
Publisher: Routledge
ISBN: 135146048X
Category : Mathematics
Languages : en
Pages : 370
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Book Description
The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.
Author: Geoffrey C. Bowker
Publisher: MIT Press
ISBN: 0262522950
Category : Science
Languages : en
Pages : 390
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Book Description
A revealing and surprising look at how classification systems can shape both worldviews and social interactions. What do a seventeenth-century mortality table (whose causes of death include "fainted in a bath," "frighted," and "itch"); the identification of South Africans during apartheid as European, Asian, colored, or black; and the separation of machine- from hand-washables have in common? All are examples of classification—the scaffolding of information infrastructures. In Sorting Things Out, Geoffrey C. Bowker and Susan Leigh Star explore the role of categories and standards in shaping the modern world. In a clear and lively style, they investigate a variety of classification systems, including the International Classification of Diseases, the Nursing Interventions Classification, race classification under apartheid in South Africa, and the classification of viruses and of tuberculosis. The authors emphasize the role of invisibility in the process by which classification orders human interaction. They examine how categories are made and kept invisible, and how people can change this invisibility when necessary. They also explore systems of classification as part of the built information environment. Much as an urban historian would review highway permits and zoning decisions to tell a city's story, the authors review archives of classification design to understand how decisions have been made. Sorting Things Out has a moral agenda, for each standard and category valorizes some point of view and silences another. Standards and classifications produce advantage or suffering. Jobs are made and lost; some regions benefit at the expense of others. How these choices are made and how we think about that process are at the moral and political core of this work. The book is an important empirical source for understanding the building of information infrastructures.
Author: David Byrne
Publisher: SAGE Publications
ISBN: 1412930510
Category : Social Science
Languages : en
Pages : 561
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Book Description
This handbook provides a clear examination of case-oriented research. It defines case-based social research as a subfield of methodology.
Author: Konstantinos V. Katsikopoulos
Publisher: MIT Press
ISBN: 0262361957
Category : Language Arts & Disciplines
Languages : en
Pages : 208
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Book Description
Rules for building formal models that use fast-and-frugal heuristics, extending the psychological study of classification to the real world of uncertainty. This book focuses on classification--allocating objects into categories--"in the wild," in real-world situations and far from the certainty of the lab. In the wild, unlike in typical psychological experiments, the future is not knowable and uncertainty cannot be meaningfully reduced to probability. Connecting the science of heuristics with machine learning, the book shows how to create formal models using classification rules that are simple, fast, and transparent and that can be as accurate as mathematically sophisticated algorithms developed for machine learning.
Author: Hariom Tatsat
Publisher: "O'Reilly Media, Inc."
ISBN: 1492073008
Category : Computers
Languages : en
Pages : 426
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Book Description
Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You'll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You'll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations
Author: Craig Martin
Publisher: Routledge
ISBN: 1315474395
Category : Religion
Languages : en
Pages : 177
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Book Description
A Critical Introduction to the Study of Religion introduces the key concepts and theories from religious studies that are necessary for a full understanding of the complex relations between religion and society. The aim is to provide readers with an arsenal of critical concepts for studying religious ideologies, practices, and communities. This thoroughly revised second edition has been restructured to clearly emphasize key topics including: Essentialism Functionalism Authority Domination. All ideas and theories are clearly illustrated, with new and engaging examples and case studies throughout, making this the ideal textbook for students approaching the subject area for the first time.
Author: Sowmya Vajjala
Publisher: O'Reilly Media
ISBN: 149205402X
Category : Computers
Languages : en
Pages : 455
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Book Description
Many books and courses tackle natural language processing (NLP) problems with toy use cases and well-defined datasets. But if you want to build, iterate, and scale NLP systems in a business setting and tailor them for particular industry verticals, this is your guide. Software engineers and data scientists will learn how to navigate the maze of options available at each step of the journey. Through the course of the book, authors Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, and Harshit Surana will guide you through the process of building real-world NLP solutions embedded in larger product setups. You’ll learn how to adapt your solutions for different industry verticals such as healthcare, social media, and retail. With this book, you’ll: Understand the wide spectrum of problem statements, tasks, and solution approaches within NLP Implement and evaluate different NLP applications using machine learning and deep learning methods Fine-tune your NLP solution based on your business problem and industry vertical Evaluate various algorithms and approaches for NLP product tasks, datasets, and stages Produce software solutions following best practices around release, deployment, and DevOps for NLP systems Understand best practices, opportunities, and the roadmap for NLP from a business and product leader’s perspective
Author: Robert J. Glushko
Publisher: "O'Reilly Media, Inc."
ISBN: 1491911719
Category : Computers
Languages : en
Pages : 743
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Book Description
Note about this ebook: This ebook exploits many advanced capabilities with images, hypertext, and interactivity and is optimized for EPUB3-compliant book readers, especially Apple's iBooks and browser plugins. These features may not work on all ebook readers. We organize things. We organize information, information about things, and information about information. Organizing is a fundamental issue in many professional fields, but these fields have only limited agreement in how they approach problems of organizing and in what they seek as their solutions. The Discipline of Organizing synthesizes insights from library science, information science, computer science, cognitive science, systems analysis, business, and other disciplines to create an Organizing System for understanding organizing. This framework is robust and forward-looking, enabling effective sharing of insights and design patterns between disciplines that weren’t possible before. The Professional Edition includes new and revised content about the active resources of the "Internet of Things," and how the field of Information Architecture can be viewed as a subset of the discipline of organizing. You’ll find: 600 tagged endnotes that connect to one or more of the contributing disciplines Nearly 60 new pictures and illustrations Links to cross-references and external citations Interactive study guides to test on key points The Professional Edition is ideal for practitioners and as a primary or supplemental text for graduate courses on information organization, content and knowledge management, and digital collections. FOR INSTRUCTORS: Supplemental materials (lecture notes, assignments, exams, etc.) are available at http://disciplineoforganizing.org. FOR STUDENTS: Make sure this is the edition you want to buy. There's a newer one and maybe your instructor has adopted that one instead.
Author: Shan Suthaharan
Publisher: Springer
ISBN: 1489976418
Category : Business & Economics
Languages : en
Pages : 364
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Book Description
This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.
