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The Outlier

By Kai Bird
  • ISBN Code: : 045149525X
  • Publisher : Crown
  • Pages : 800
  • Category : Biography & Autobiography
  • Reads : 105
  • Book Compatibility : Pdf, ePub, Mobi, Kindle
  • Pdf : the-outlier.pdf

Book Excerpt :

“Important . . . [a] landmark presidential biography . . . Bird is able to build a persuasive case that the Carter presidency deserves this new look.”—The New York Times Book Review An essential re-evaluation of the complex triumphs and tragedies of Jimmy Carter’s presidential legacy—from the expert biographer and Pulitzer Prize–winning co-author of American Prometheus Four decades after Ronald Reagan’s landslide win in 1980, Jimmy Carter’s one-term presidency is often labeled a failure; indeed, many Americans view Carter as the only ex-president to have used the White House as a stepping-stone to greater achievements. But in retrospect the Carter political odyssey is a rich and human story, marked by both formidable accomplishments and painful political adversity. In this deeply researched, brilliantly written account, Pulitzer Prize–winning biographer Kai Bird deftly unfolds the Carter saga as a tragic tipping point in American history. As president, Carter was not merely an outsider; he was an outlier. He was the only president in a century to grow up in the heart of the Deep South, and his born-again Christianity made him the most openly religious president in memory. This outlier brought to the White House a rare mix of humility, candor, and unnerving self-confidence that neither Washington nor America was ready to embrace. Decades before today’s public reckoning with the vast gulf between America’s ethos and its actions, Carter looked out on a nation torn by race and demoralized by Watergate and Vietnam and prescribed a radical self-examination from which voters recoiled. The cost of his unshakable belief in doing the right thing would be losing his re-election bid—and witnessing the ascendance of Reagan. In these remarkable pages, Bird traces the arc of Carter’s administration, from his aggressive domestic agenda to his controversial foreign policy record, taking readers inside the Oval Office and through Carter’s battles with both a political establishment and a Washington press corps that proved as adversarial as any foreign power. Bird shows how issues still hotly debated today—from national health care to growing inequality and racism to the Israeli-Palestinian conflict—burned at the heart of Carter’s America, and consumed a president who found a moral duty in solving them. Drawing on interviews with Carter and members of his administration and recently declassified documents, Bird delivers a profound, clear-eyed evaluation of a leader whose legacy has been deeply misunderstood. The Outlier is the definitive account of an enigmatic presidency—both as it really happened and as it is remembered in the American consciousness.

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Book Short Summary:

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  • Pdf File: outliers-in-control-engineering.pdf

Book Short Summary:

Outliers play an important, though underestimated, role in control engineering. Traditionally they are unseen and neglected. In opposition, industrial practice gives frequent examples of their existence and their mostly negative impacts on the control quality. The origin of outliers is never fully known. Some of them are generated externally to the process (exogenous), like for instance erroneous observations, data corrupted by control systems or the effect of human intervention. Such outliers appear occasionally with some unknow probability shifting real value often to some strange and nonsense value. They are frequently called deviants, anomalies or contaminants. In most cases we are interested in their detection and removal. However, there exists the second kind of outliers. Quite often strange looking data observations are not artificial data occurrences. They may be just representatives of the underlying generation mechanism being inseparable internal part of the process (endogenous outliers). In such a case they are not wrong and should be treated with cautiousness, as they may include important information about the dynamic nature of the process. As such they cannot be neglected nor simply removed. The Outlier should be detected, labelled and suitably treated. These activities cannot be performed without proper analytical tools and modeling approaches. There are dozens of methods proposed by scientists, starting from Gaussian-based statistical scoring up to data mining artificial intelligence tools. The research presented in this book presents novel approach incorporating non-Gaussian statistical tools and fractional calculus approach revealing new data analytics applied to this important and challenging task. The proposed book includes a collection of contributions addressing different yet cohesive subjects, like dynamic modelling, classical control, advanced control, fractional calculus, statistical analytics focused on an ultimate goal: robust and outlier-proof analysis. All studied problems show that outliers play an important role and classical methods, in which outlier are not taken into account, do not give good results. Applications from different engineering areas are considered such as semiconductor process control and monitoring, MIMO peltier temperature control and health monitoring, networked control systems, and etc.

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Book Short Summary:

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Book Short Summary:

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Book Short Summary:

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 naïve Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.

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  • Pdf File: computer-supported-cooperative-work-and-social-computing.pdf

Book Short Summary:

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Book Short Summary:

A significant amount of academic research his conducted using quantitative research methods. In many universities large and expensive statistical software has been acquired. However much of this software requires a considerable amount of training before researchers are capable of using it correctly and this can cause difficulties. Many academic researchers are surprised by just how much analytical work can be done using the ubiquitous Microsoft Excel software. This book presents a course on the use of statistics in academic research starting with simple descriptive techniques and working through to sophisticated inferential methods. A step-by-step approach has been taken and has been described by users of this book as similar to having the teacher standing by you as you learn about some of the sophisticated methods of handling and understanding data. Readers of this book have my best wishes in achieving their objectives through their work with academic research.

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Book Short Summary:

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Book Short Summary:

All too often, individuals engaged in the biomedical sciences assume that numeric data must be left to the proper authorities (e.g., statisticians and data analysts) who are trained to apply sophisticated mathematical algorithms to sets of data. This is a terrible mistake. Individuals with keen observational skills, regardless of their mathematical training, are in the best position to draw correct inferences from their own data and to guide the subsequent implementation of robust, mathematical analyses. Volume 2 of Logic and Critical Thinking in the Biomedical Sciences provides readers with a repertoire of deductive non-mathematical methods that will help them draw useful inferences from their own data. Volumes 1 and 2 of Logic and Critical Thinking in the Biomedical Sciences are written for biomedical scientists and college-level students engaged in any of the life sciences, including bioinformatics and related data sciences. Demonstrates that a great deal can be deduced from quantitative data, without applying any statistical or mathematical analyses Provides readers with simple techniques for quickly reviewing and finding important relationships hidden within large and complex sets of data Using examples drawn from the biomedical literature, discusses common pitfalls in data interpretation and how they can be avoided

An Introduction to Statistics using Microsoft Excel 2nd Edition

By Dan Remenyi,George Onofrei,Joseph English
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Book Short Summary:

The handling of numbers in arithmetic and the progression into the more abstract field of mathematics and statistics is generally approached poorly in our education system. The inadequacy is not necessarily in the teaching techniques or the books and other text used but rather in the attitude towards these subjects. These subjects are seen as something which has to be taught because it is part of a preordained curriculum rather than a set of tools which are available to help people live a fuller, more productive and more interesting life. It is so enlightening when one hears people say, "I thought that when I left school I was leaving all the maths stuff behind me!" or "I was bored witless by all those numbers and formulas [sic] that were forced down my throat." This book was written out of a frustration at seeing statistics taught through formal methods using large scale statistic software packages. It seemed to me that very little was learned by this process and quite often both the teachers and the students were in denial. It is true that the students were generally able to pick up enough knowledge to pass an examination or to complete a piece of research. But I seldom saw anything which could be regarded as deep learning and the little which had been learned did not stay for any length of time in the heads of these learners. I know people who have passed several university level courses in statistics and they can hardly recall never mind use any of what was taught to them.

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Book Short Summary:

This book constitutes the refereed proceedings of the 5th International Conference on Web-Age Information Management, WAIM 2004, held in Dalian, China in July 2004. The 57 revised full papers and 23 revised short and industrial papers presented together with 3 invited contributions were carefully reviewed and selected from 291 submissions. The papers are organized in topical sections on data stream processing, time series data processing, security, mobile computing, cache management, query evaluation, Web search engines, XML, Web services, classification, and data mining.

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  • Pdf File: advanced-data-mining-and-applications.pdf

Book Short Summary:

This book constitutes the refereed proceedings of the 8th International Conference on Advanced Data Mining and Applications, ADMA 2012, held in Nanjing, China, in December 2012. The 32 regular papers and 32 short papers presented in this volume were carefully reviewed and selected from 168 submissions. They are organized in topical sections named: social media mining; clustering; machine learning: algorithms and applications; classification; prediction, regression and recognition; optimization and approximation; mining time series and streaming data; Web mining and semantic analysis; data mining applications; search and retrieval; information recommendation and hiding; outlier detection; topic modeling; and data cube computing.

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  • Book Code : 1118031229
  • Total of Pages : 496
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  • Pdf File: a-course-in-time-series-analysis.pdf

Book Short Summary:

New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include: Contributions from eleven of the worldâ??s leading figures in time series Shared balance between theory and application Exercise series sets Many real data examples Consistent style and clear, common notation in all contributions 60 helpful graphs and tables Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis. An Instructor's Manual presenting detailed solutions to all the problems in he book is available upon request from the Wiley editorial department.

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  • Publisher : Springer Science & Business Media
  • Book Code : 3642217621
  • Total of Pages : 1038
  • Category : Technology & Engineering
  • Members : 825
  • Pdf File: communication-systems-and-information-technology.pdf

Book Short Summary:

This volume includes extended and revised versions of a set of selected papers from the International Conference on Electric and Electronics (EEIC 2011) , held on June 20-22 , 2011, which is jointly organized by Nanchang University, Springer, and IEEE IAS Nanchang Chapter. The objective of EEIC 2011 Volume 4 is to provide a major interdisciplinary forum for the presentation of new approaches from Communication Systems and Information Technology, to foster integration of the latest developments in scientific research. 137 related topic papers were selected into this volume. All the papers were reviewed by 2 program committee members and selected by the volume editor Prof. Ming Ma. We hope every participant can have a good opportunity to exchange their research ideas and results and to discuss the state of the art in the areas of the Communication Systems and Information Technology.

Computer Analysis of Images and Patterns

By Mario Vento,Gennaro Percannella
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : Springer Nature
  • Book Code : 3030298884
  • Total of Pages : 688
  • Category : Computers
  • Members : 443
  • Pdf File: computer-analysis-of-images-and-patterns.pdf

Book Short Summary:

The two volume set LNCS 11678 and 11679 constitutes the refereed proceedings of the 18th International Conference on Computer Analysis of Images and Patterns, CAIP 2019, held in Salerno, Italy, in September 2019. The 106 papers presented were carefully reviewed and selected from 176 submissions The papers are organized in the following topical sections: Intelligent Systems; Real-time and GPU Processing; Image Segmentation; Image and Texture Analysis; Machine Learning for Image and Pattern Analysis; Data Sets and Benchmarks; Structural and Computational Pattern Recognition; Posters.

Hyperspectral Image Processing

By Liguo Wang,Chunhui Zhao
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : Springer
  • Book Code : 3662474565
  • Total of Pages : 315
  • Category : Technology & Engineering
  • Members : 203
  • Pdf File: hyperspectral-image-processing.pdf

Book Short Summary:

Based on the authors’ research, this book introduces the main processing techniques in hyperspectral imaging. In this context, SVM-based classification, distance comparison-based endmember extraction, SVM-based spectral unmixing, spatial attraction model-based sub-pixel mapping and MAP/POCS-based super-resolution reconstruction are discussed in depth. Readers will gain a comprehensive understanding of these cutting-edge hyperspectral imaging techniques. Researchers and graduate students in fields such as remote sensing, surveying and mapping, geosciences and information systems will benefit from this valuable resource.

Biostatistics: An Applied Introduction for the Public Health Practitioner

By Heather M. Bush
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : Cengage Learning
  • Book Code : 1133708951
  • Total of Pages : 608
  • Category : Education
  • Members : 532
  • Pdf File: biostatistics.pdf

Book Short Summary:

BIOSTATISTICS: AN APPLIED INTRODUCTION FOR THE PUBLIC HEALTH PRACTITIONER is designed to help public health researchers, practitioners, and students understand and apply essential biostatistics concepts. This innovative new text emphasizes real-world public health problems and the research questions they inspire. This text provides a unique introduction to statistical concepts and methods used by working professionals during investigations. Unlike other texts that assume a strong knowledge of mathematics or rely heavily on formulas, BIOSTATISTICS consistently emphasizes the public health context, making even complex material both accessible and relevant. The first chapter introduces common statistical terminology by explaining them in clear language, while subsequent chapters explore the most useful and versatile statistical methods for a variety of public health research questions. For each type of question, the author presents a range of applicable methods, from descriptions of data to simple statistical tests, generalized linear models, and multiple variable regression. The text's step-by-step coverage of fundamental concepts is perfect for students new to the field, but its depth and detail also make it ideal for two-course series in M.P.H. or M.H.A. programs, or for working professionals. Readers at all stages of their professional lives can draw on this invaluable resource to help them interpret and conduct statistical studies and support effective evidence-based practice. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Fitting Models to Biological Data Using Linear and Nonlinear Regression

By Harvey Motulsky,Arthur Christopoulos
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : Oxford University Press
  • Book Code : 9780198038344
  • Total of Pages : 352
  • Category : Science
  • Members : 127
  • Pdf File: fitting-models-to-biological-data-using-linear-and-nonlinear-regression.pdf

Book Short Summary:

Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.

Big Data

By Balamurugan Balusamy,Nandhini Abirami R,Seifedine Kadry,Amir H. Gandomi
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : John Wiley & Sons
  • Book Code : 1119701872
  • Total of Pages : 368
  • Category : Mathematics
  • Members : 617
  • Pdf File: big-data.pdf

Book Short Summary:

Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.

An Introduction to SAS Visual Analytics

By Tricia Aanderud,Rob Collum,Ryan Kumpfmiller
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : SAS Institute
  • Book Code : 1635260442
  • Total of Pages : 294
  • Category : Computers
  • Members : 527
  • Pdf File: an-introduction-to-sas-visual-analytics.pdf

Book Short Summary:

Focusing on the version of SAS Visual Analytics on SAS 9.4, this thorough guide will show you how to make sense of your complex data with the goal of leading you to smarter, data-driven decisions without having to write a single line of code ¿̐ư unless you want to. --

Emerging Technologies in Data Mining and Information Security

By Ajith Abraham,Paramartha Dutta,Jyotsna Kumar Mandal,Abhishek Bhattacharya,Soumi Dutta
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : Springer
  • Book Code : 9811314985
  • Total of Pages : 885
  • Category : Technology & Engineering
  • Members : 224
  • Pdf File: emerging-technologies-in-data-mining-and-information-security.pdf

Book Short Summary:

The book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018) held at the University of Engineering & Management, Kolkata, India, on February 23–25, 2018. It comprises high-quality research by academics and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, case studies related to all the areas of data mining, machine learning, IoT and information security.

Computational Intelligence and Intelligent Systems

By Hu Peng,Changshou Deng,Zhijian Wu,Yong Liu
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : Springer
  • Book Code : 9811364737
  • Total of Pages : 378
  • Category : Computers
  • Members : 830
  • Pdf File: computational-intelligence-and-intelligent-systems.pdf

Book Short Summary:

This book constitutes the thoroughly refereed proceedings of the 10th International Symposium, ISICA 2018, held in Jiujiang, China, in October 2018.The 32 full papers presented were carefully reviewed and selected from 83 submissions. The papers are organized in topical sections on nature-inspired computing; bio-inspired computing; novel operators in evolutionary algorithms; automatic object segmentation and detection; and image colorization; multilingual automatic document classication and translation; knowledge-based articial intelligence; predictive data mining.

The Scattering

By Kimberly McCreight
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : HarperCollins
  • Book Code : 0062359142
  • Total of Pages : 320
  • Category : Young Adult Fiction
  • Members : 599
  • Pdf File: the-scattering.pdf

Book Short Summary:

New York Times bestselling author Kimberly McCreight raises the stakes in the second book of the heart-pounding Outliers trilogy, a uniquely speculative story about secrets, betrayal, and a world where one small group of people are blessed—or cursed—with an incredible power. Wylie may have escaped the camp in Maine, but she is far from safe. The best way for her to protect herself is to understand her ability, fast. But after spending a lifetime trying to ignore her own feelings, giving in to her ability to read other peoples’ emotions is as difficult as it is dangerous. And Wylie isn’t the only one at risk. Ever since they returned home, Jasper has been spiraling, wracked with guilt over what happened to Cassie. After all they’ve been through together, Wylie and Jasper would do anything for each other, but she doesn’t know if their bond is strong enough to overcome demons from the past. It is amid this uncertainty and fear that Wylie finds herself confronted with a choice. She was willing to do whatever it took to help Cassie, but is she prepared to go to the same extremes to help complete strangers . . . even if they are just like her?

Machine Learning and Knowledge Discovery in Databases

By Peter A. Flach,Tijl De Bie,Nello Cristianini
  • File : Pdf, ePub, Mobi, Kindle
  • Publisher : Springer
  • Book Code : 3642334865
  • Total of Pages : 867
  • Category : Computers
  • Members : 624
  • Pdf File: machine-learning-and-knowledge-discovery-in-databases.pdf

Book Short Summary:

This two-volume set LNAI 7523 and LNAI 7524 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2012, held in Bristol, UK, in September 2012. The 105 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 443 submissions. The final sections of the proceedings are devoted to Demo and Nectar papers. The Demo track includes 10 papers (from 19 submissions) and the Nectar track includes 4 papers (from 14 submissions). The papers grouped in topical sections on association rules and frequent patterns; Bayesian learning and graphical models; classification; dimensionality reduction, feature selection and extraction; distance-based methods and kernels; ensemble methods; graph and tree mining; large-scale, distributed and parallel mining and learning; multi-relational mining and learning; multi-task learning; natural language processing; online learning and data streams; privacy and security; rankings and recommendations; reinforcement learning and planning; rule mining and subgroup discovery; semi-supervised and transductive learning; sensor data; sequence and string mining; social network mining; spatial and geographical data mining; statistical methods and evaluation; time series and temporal data mining; and transfer learning.