The Concept Of Model

In "The Concept of Model" Alain Badiou establishes a new logical 'concept of model'. Translated for the first time into English, the work is accompanied by an exclusive interview with Badiou in which he elaborates on the connections between his early and most recent work--for which the concept of model remains seminal.

In The Concept of Model Alain Badiou establishes a new logical 'concept of model'. Translated for the first time into English, the work is accompanied by an exclusive interview with Badiou in which he elaborates on the connections between his early and most recent work-for which the concept of model remains seminal.

Models in Microeconomic Theory covers basic models in current microeconomic theory. Part I (Chapters 1-7) presents models of an economic agent, discussing abstract models of preferences, choice, and decision making under uncertainty, before turning to models of the consumer, the producer, and monopoly. Part II (Chapters 8-14) introduces the concept of equilibrium, beginning, unconventionally, with the models of the jungle and an economy with indivisible goods, and continuing with models of an exchange economy, equilibrium with rational expectations, and an economy with asymmetric information. Part III (Chapters 15-16) provides an introduction to game theory, covering strategic and extensive games and the concepts of Nash equilibrium and subgame perfect equilibrium. Part IV (Chapters 17-20) gives a taste of the topics of mechanism design, matching, the axiomatic analysis of economic systems, and social choice. The book focuses on the concepts of model and equilibrium. It states models and results precisely, and provides proofs for all results. It uses only elementary mathematics (with almost no calculus), although many of the proofs involve sustained logical arguments. It includes about 150 exercises. With its formal but accessible style, this textbook is designed for undergraduate students of microeconomics at intermediate and advanced levels.

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Discover the secrets of the Google SketchUp with the 16 real-world professional-level projects including parks, structures, concept art, and illustration. Google SketchUp Workshop includes all the wide variety of projects that SketchUp can be used for-architectural visualization, landscape design, video game and film conception, and more. SketchUp masters in every field will get you up to speed in this agile and intuitive software and then show you the real uses with through projects in architecture, engineering, and design.

Marx Wartofsky has been working for many years within an unusual confluence of philosophical problems. He brings to these intersecting problems his comprehensive intelligence, at once imaginative and rigorous, analytic and historical. He is a philosopher's philosopher, but also Everyman's. Wartofsky is philosopher of the natural and the social sciences, of perception, esthetics and the creative arts, of the 18th century French and the 19th century Germans, of politics and morality, ofthe methods and morals of medicine, and it is plain, of all human existence. To a colleague, he seems Jack-of-all-philosophical-trades, and master of them too. The reader soon will learn that Wartofsky is a genial, lucid and relaxed philosophical companion, deeply serious but without noticeable anxiety. I need not highlight these selected epistemological papers gathered as, and about, Models, since Wartofsky's own introductory remarks are helpful and stimulating in that respect. I need only, after 21 years of friendship and collaboration with him, warn the reader to beware of how profound and provocative these papers will show themselves to be beneath their good-humored and swiftly-flowing surface. And I must publicly note the pleasure with which I welcome Marx Wartofsky's volume to our Boston Studies. Boston University R.S.C. Center for the Philosophy and History of Science September 1979 vii TABLE OF CONTENTS EDITORIAL PREFACE VII xi AC K NOWLEDGEMENTS xiii INTRODUCTION The Model Muddle: Proposals for an Immodest Realism 1.

Discover the essential thinking tools you’ve been missing with The Great Mental Models series by Shane Parrish, New York Times bestselling author and the mind behind the acclaimed Farnam Street blog and “The Knowledge Project” podcast. This first book in the series is your guide to learning the crucial thinking tools nobody ever taught you. Time and time again, great thinkers such as Charlie Munger and Warren Buffett have credited their success to mental models–representations of how something works that can scale onto other fields. Mastering a small number of mental models enables you to rapidly grasp new information, identify patterns others miss, and avoid the common mistakes that hold people back. The Great Mental Models: Volume 1, General Thinking Concepts shows you how making a few tiny changes in the way you think can deliver big results. Drawing on examples from history, business, art, and science, this book details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making and productivity. This book will teach you how to: Avoid blind spots when looking at problems. Find non-obvious solutions. Anticipate and achieve desired outcomes. Play to your strengths, avoid your weaknesses, … and more. The Great Mental Models series demystifies once elusive concepts and illuminates rich knowledge that traditional education overlooks. This series is the most comprehensive and accessible guide on using mental models to better understand our world, solve problems, and gain an advantage.