Author: Annie M. Brewer
Publisher:
Published: 1988
Total Pages: 1333
ISBN-13: 9780810304406
DOWNLOAD EBOOK →Author: Annie M. Brewer
Publisher: Gale Research International, Limited
Published: 1979
Total Pages: 592
ISBN-13:
DOWNLOAD EBOOK →Author: Annie M. Brewer
Publisher: Detroit : Gale Research Company
Published: 1979
Total Pages: 771
ISBN-13: 9780810311305
DOWNLOAD EBOOK →Author: Peter Mark Roget
Publisher: Taylor & Francis
Published: 1997
Total Pages: 548
ISBN-13: 9780425156681
DOWNLOAD EBOOK →Roget's II: The New Thesaurus, Third Edition, is the essential writing tool for every classroom, home, and office, providing all the features that have made Roget's a trusted name for 100 years. The most accessible and easy-to-use thesaurus available, Roget's II includes: Clear, accurate definitions for every synonym group, so you can find just the word you're looking for. Complete alphabetical listing of all synonyms, fully cross-referenced to the main entries. Unique category index of related words and words of opposite meaning to expand and enrich your word choices. With 35,000 synonyms listed and defined, Roget's II is an effective tool for students, writers, professionals, or anyone searching for just the right word!
Author: Annie M. Brewer
Publisher: Detroit, Mich. : Gale Research Company
Published: 1982
Total Pages: 552
ISBN-13:
DOWNLOAD EBOOK →Author: Donald Ary
Publisher:
Published: 2006
Total Pages: 0
ISBN-13: 9780495008057
DOWNLOAD EBOOK →An introduction to research in education text, this book helps students to master the basic competencies necessary to understand and evaluate the research of others, and shows them how to plan and conduct original research.
Author: Jonas Peters
Publisher: MIT Press
Published: 2017-11-29
Total Pages: 289
ISBN-13: 0262037319
DOWNLOAD EBOOK →A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.
Author: M. E. D'Imperio
Publisher:
Published: 1978
Total Pages: 164
ISBN-13:
DOWNLOAD EBOOK →In spite of all the papers that others have written about the manuscript, there is no complete survey of all the approaches, ideas, background information and analytic studies that have accumulated over the nearly fifty-five years since the manuscript was discovered by Wilfrid M. Voynich in 1912. This report pulls together all the information the author could obtain from all the sources she has examined, and to present it in an orderly fashion. The resulting survey will provide a firm basis upon which other students may build their work, whether they seek to decipher the text or simply to learn more about the problem.