The first comprehensive introduction to benchmarking, the engine behind progress in AIIn machine learning, researchers split their data into training and test sets, let model builders compete on the test set, and call it a benchmark. Statistical tradition prescribed locking test sets in a vault, but machine learning practitioners shared them freely. Benchmarking shouldn’t have worked, but it did, and the machine learning community never figured out the science behi...

An introduction to the intellectual foundations and practical utility of the recent work on fairness and machine learning.Fairness and Machine Learning introduces advanced undergraduate and graduate students to the intellectual foundations of this recently emergent field, drawing on a diverse range of disciplinary perspectives to identify the opportunities and hazards of automated decision-making. It surveys the risks in many applications of machine learning and pr...

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for ...

Despite the swift spread of social network concepts and their applications and the rising use of network analysis in social science, there is no book that provides a thorough general introduction for the serious reader. Understanding Social Networks fills that gap by explaining the big ideas that underlie the social network phenomenon. Written for those interested in this fast moving area but who are not mathematically inclined, it covers fundamental concepts, then discusses netwo...

"Statistical Methods in Online A/B Testing" is a comprehensive guide to statistics in online controlled experiments, a.k.a. A/B tests, that tackles the difficult matter of statistical inference in a way accessible to readers with little to no prior experience with it. Each concept is built from the ground up, explained thoroughly, and illustrated with practical examples from website testing.The presentation is straight to the point and practically oriented so you can apply the take...

ARTIFICIAL INTELLIGENCE FOR BEGINNERS: Get a concise, informative overview of AI ethics and policy—and how it could impact our society.Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring home-owners, students, educators, patients, clients, prison inmates, membe...

Use Product Analytics to Understand Consumer Behavior and Change It at ScaleProduct Analytics is a complete, hands-on guide to generating actionable business insights from customer data. Experienced data scientist and enterprise manager Joanne Rodrigues introduces practical statistical techniques for determining why things happen and how to change what people do at scale. She complements these with powerful social science techniques for cr...

Massive amounts of data on human beings can now be analyzed. Pragmatic purposes abound, including selling goods and services, winning political campaigns, and identifying possible terrorists. Yet 'big data' can also be harnessed to serve the public good: scientists can use big data to do research that improves the lives of human beings, improves government services, and reduces taxpayer costs. In order to achieve this goal, researchers must have access to this data - raising important priv...

This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the "big themes" of the discipline—machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one.Taken as a whole, the lesso...

Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets.Human-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, ana...

Social Network Theory and Educational Change offers a provocative and fascinating exploration of how social networks in schools can impede or facilitate the work of education reform.Drawing on the work of leading scholars, the book comprises a series of studies examining networks among teachers and school leaders, contrasting formal and informal organizational structures, and exploring the mechanisms by which ideas, information, and influence flow from per...

This book synthesizes a decade of research by the author into fundamental issues in organization design. The result is a novel micro-structural perspective on organizations, which aims to both expand and narrow current thinking. The new perspective takes an expansive view on the kinds of phenomena that can be studied in terms of organization design- such as cross-functional teams, strategic partnerships, buyer-supplier relations, alliance networks, mega-projects, post-merger integration, b...